jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jongbok Lee
Source: OakTrust (Texas A&M University Libraries) (article, 2018-07-19)
Field: Chemistry — Inorganic Chemistry

Thermodynamic Synthesis of Ladder-Type Functional Organic Materials Conjugated ladder-type macromolecules with coplanar, sp2 atom-rich backbones represent a captivating class of materials on account of their well-defined rigid structures, intriguing syntheses, and promising potential in optoelectronic applications. The ladder-type backbones possess an intrinsically rigid conformation and limit possible torsional disorder. The unique architecture of conjugated ladder-type material leads to extended π-conjugation length, longer exciton diffusion length, and enhanced stability. In contrast, conventional conjugated polymers have intrinsic torsional disorder which partially break the conjugation pathways of the polymers and could be detrimental to the material properties. \nSeveral preliminary literature examples have demonstrated the synthesis of ladder-type materials. However, it is still challenging to synthesize well-defined ladder polymers with a minimum level of structural defects because of the poor product solubility and limited synthetic methods. In order to overcome these obstacles, a highly efficient synthetic method and a rationally designed structural characteristic that enables solubility need to be accomplished simultaneously. \nWe envisioned that thermodynamically controlled ring-closing olefin metathesis (RCM) held the promise for a highly efficient and synthesis of conjugated ladder polymers with minimum levels of structural defects due to the strong thermodynamic driving force of aromatization and its reversible nature between starting material and side products. Moreover, the mild reaction conditions allow a wider scope of substrates and excellent \nfunctional group tolerance. This efficient and versatile synthetic strategy successfully afforded various fused polycyclic heteroarenes, a series of extended ladder-type oligomers, and conjugated ladder polymers with minimum levels of structural defects in excellent yields. Furthermore, RCM demonstrated an excellent ring annulation efficiency with electron deficient acceptor units. Due to the good solubility of the ladder-type materials originating from orthogonally adopted α-branched solubilizing group, the properties of the desired materials were rigorously investigated in solution and the solid-state, such as photophysical properties, solid-state conformation and morphology, effective conjugation length, formation of charge transfer complexes, and crystallization dynamics. This research provides a well-established synthetic strategy to construct a fully conjugated ladder-type material and a fundamental understanding of ladder-type functional organic materials for potential future applications in electronic and optoelectronic devices. Chemistry ; Materials science ; Chemical engineering ; Engineering Zeolite Catalysis and Synthesis ; Catalysis and Oxidation Reactions ; Machine Learning in Materials Science
Authors: Sarah E. Davis
Source:  (article, 2018-11-20)
Field: Materials Science — Materials Chemistry

Data Driven Methods for Chemical Process and Product Synthesis and Design Process engineering ; Process (computing) ; Product (mathematics) ; Computer science ; Process management ; Biochemical engineering ; Business ; Engineering ; Mathematics ; Programming language Machine Learning in Materials Science ; Innovative Microfluidic and Catalytic Techniques Innovation ; Advanced Control Systems Optimization
Authors: Thuong Nguyen | Eszter Székely | Giulio Imbalzano | Jörg Behler | Gábor Cśanyi | Michele Ceriotti | Andreas Goetz | Francesco Paesani
Source: Cambridge University Engineering Department Publications Database (article, 2018-08-19)
Field: Materials Science — Materials Chemistry

Data-driven many-body representations with chemical accuracy for molecular simulations from the gas to the condensed phase COSMO Gas phase ; Phase (matter) ; Statistical physics ; Computer science ; Chemistry ; Physics ; Thermodynamics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Phase Equilibria and Thermodynamics
Authors: 尹海清 | Jiang Zhao Xue | 刘国权 | Sharon | Elder | 徐斌 | 郑清军 | 曲选辉
Source: Chinese Physics B (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

The materials data ecosystem： Materials data science and its role in data-driven materials discovery Data science ; Computer science ; Materials science Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Electron and X-Ray Spectroscopy Techniques
Authors: Jinbo Pan | Haowei Peng | Hua Wang | Jie Yu | Huta Banjade | Xiaofeng Qian | John P. Perdew | Qimin Yan
Source: Bulletin of the American Physical Society (article, 2018-03-09)
Field: Materials Science — Materials Chemistry

Data-driven discovery of functional 2D materials utilizing a computational database for electronic structures Computer science ; Database Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques
Authors: Gowoon Cheon | Karel-Alexander N. Duerloo | Austin D. Sendek | Chase Porter | Yuan Chen | Evan J. Reed
Source: Bulletin of the American Physical Society (article, 2018-03-06)
Field: Materials Science — Materials Chemistry

Data-driven Discovery of New Two- and One-dimensional Materials and Lattice-commensurate Heterostructures Heterojunction ; Lattice (music) ; Materials science ; Condensed matter physics ; Physics Machine Learning in Materials Science ; Nanocluster Synthesis and Applications ; Catalysis and Oxidation Reactions
Authors: Oliver Marquardt | Peter Mathé | Thomas Koprucki | A. Miguel | Morten Willatzen
Source:  (article, 2018-11-01)
Field: Materials Science — Materials Chemistry

Data-driven electronic structure calculations in semiconductor nanostructures — beyond the eight-band k · p formalism In this work, we present a scheme to extract electronic structure parameters for multi-band k · p models beyond the well-established eight-band approach using up-to-date ab initio band structures. Our scheme allows us to identify parameters for k · p models with Hamiltonian matrices of arbitrary complexity and level of sophistication. The computational effort of our approach is very small and increases only slightly with the number of parameters that need to be fitted. We can furthermore apply priorities to specific bands or high-symmetry points of the Brillouin zone and can incorporate routines that help to increase the numerical stability of electronic structure simulations of semiconductor nanostructures using the obtained parameter sets. Brillouin zone ; Electronic structure ; Hamiltonian (control theory) ; Semiconductor ; Electronic band structure ; Band gap ; Semiconductor nanostructures ; Formalism (music) ; Ab initio ; Statistical physics ; Sophistication ; Physics ; Materials science ; Computational physics ; Computer science ; Condensed matter physics ; Mathematics ; Quantum mechanics ; Mathematical optimization Machine Learning in Materials Science ; 2D Materials and Applications ; Ga2O3 and related materials
Authors: Ying‐Hao Chu
Source: ECS Meeting Abstracts (article, 2018-07-23)
Field: Materials Science — Materials Chemistry

(Invited) Oxide Heteroepitaxy for Soft Technology A new world is being formed based on the technologies composed of artificial intelligence, Internet of Things (IoT), and robot systems. Especially, in the research fields of IoT and robot systems, a device with mechanical flexibility can deliver more degrees of freedom on design of the systems. Therefore, the development of soft and flexible electronics becomes an important research direction for wearable and IoT devices. Due to the mechanical flexibility, polymers materials and thin foils made of metals are commonly used in the fabrication of flexible electronic systems. However, the reliability issue under practical operation hinders the applications of these flexible electronics, especially those on polymer substrates. This is attributed to a mismatch of thermal expansion coefficient between substrate and functional materials or low thermal and chemical endurance of polymers and organic materials. A lot of researchers are working hard and together to expand the applicability of current flexible devices. However, new pathway to flexible electronics can also be developed in parallel to provide more subtle solutions, thus needing new platform to integrate functional materials with good thermal and chemical stabilities together with mechanical flexibility. Recently, due to the quick rise of growth facilities, various techniques are employed to acquire flexible oxide heteroepitaxy. In this talk, I will highlight the methods to develop oxide heteroepitaxy with mechanical flexibility, including direct and indirect approaches. I will also provide an overview that classifies the application fields where flexible oxide heteroepitaxy have been adopted and the approach which has been used to develop particular oxide with the emphasis on electronic and photonic devices. Flexibility (engineering) ; Electronics ; Flexible electronics ; Computer science ; Nanotechnology ; Wearable technology ; Stretchable electronics ; Wearable computer ; Materials science ; Mechanical engineering ; Engineering ; Embedded system ; Electrical engineering Chemical and Physical Properties of Materials ; Machine Learning in Materials Science ; Transition Metal Oxide Nanomaterials
Authors: Kyosuke Sato | Satoshi Ohmura | Kenji Tsuruta
Source: The Japan Society of Applied Physics (article, 2018-07-10)
Field: Materials Science — Materials Chemistry

Data-Driven Organic Molecule Design for Optimization of Physical Properties Materials science ; Organic molecules ; Molecule ; Nanotechnology ; Organic chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Fuel Cells and Related Materials
Authors: Thorsten Gressling
Source: ChemRxiv (preprint, 2018-10-29)
Field: Chemistry — Physical and Theoretical Chemistry

Autochemistry: A Research Paradigm Based on Artificial Intelligence and Big Data Artificial Intelligence technologies affect every domain and process in industry. Many solutions with different maturity levels have been created or are in development. With this paper we collect initiatives in the domain of chemical science and bring these resources together into a common process model. &lt;div&gt;We define ten building blocks, analyse their role in the architecture and evaluate their impact to the current system. Finally we discuss the changes and the transition that occurs to the lab worker and the chemist.&lt;br&gt;&lt;/div&gt;&lt;div&gt;This paper introduces &lt;i&gt;Autochemistry&lt;/i&gt; as a meme and for further development and discussion. We just can provide a first sketch to this exciting new area of scientific principles changing the anthropocentric fundament of chemistry research to a technocentric one.&lt;br&gt;&lt;/div&gt; Sketch ; Domain (mathematical analysis) ; Anthropocentrism ; Process (computing) ; Architecture ; Maturity (psychological) ; Computer science ; Data science ; Artificial intelligence ; Political science ; Mathematics ; Art ; Algorithm ; Law History and advancements in chemistry ; Computational Drug Discovery Methods ; Machine Learning in Materials Science
Authors: Eric A. Stach | Benji Maruyama | Chaomei Chen
Source: Microscopy and Microanalysis (article, 2018-08-01)
Field: Materials Science — Materials Chemistry

Using Operando Characterization, Data Analytics, and Artificial Intelligence to Understand Mechanistic Links between Processing and Structure In this presentation, we will describe a vision for a future research paradigm, wherein a tight coupling of in-situ and operando experimental methods, data analytics and automated data analysis are coupled with artificial intelligence to direct how we use electron microscopy (and other forms of materials characterization) to characterize the mechanisms by which processing/structure/property relationships are determined. The presentation will be forward looking and will incorporate research results and ideas culled from a variety of sources and authors: it will not be a typical presentation reviewing research from just the co-authors. Characterization (materials science) ; Analytics ; Data analysis ; Data science ; Computer science ; Business intelligence ; Materials science ; Data mining ; Nanotechnology Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Memory and Neural Computing
Authors: Linda Wang﻿
Source: C&EN Global Enterprise (article, 2018-11-12)
Field: Chemistry — Physical and Theoretical Chemistry

Ernest W. Robb Ernest W. Robb, 86, died on Aug. 31 in Glen Rock, N.J. “Ernest taught at Stevens Institute of Technology for 32 years, engaging a generation of students with his clear, committed, and dynamic teaching. He also led the faculty council three times and led Stevens’s American Association of University Professors’ first and only strike. He pioneered the use of artificial intelligence for identifying unknown organic compounds. A Renaissance man, he loved music and studied everything from archaeology to mythology to poetry to linguistics. He was intensely curious and analytical about everything he encountered, from how U.S. politics works to why languages have pronouns. He was also a remarkably kind, gentle, and reliable person.”—John Robb, son Most recent title: Professor, Stevens Institute of Technology Education: B.S., chemistry, Kansas State University, 1952; Ph.D., chemistry, Harvard University, 1956 Survivors: Sons, Arthur, John, and William To recognize your late loved one or colleague, submit Art History and advancements in chemistry ; Twentieth Century Scientific Developments ; Various Chemistry Research Topics
Authors: Youhei Yamaji
Source: JPSJ News and Comments (article, 2018-01-15)
Field: Materials Science — Materials Chemistry

Making Data-Driven Curie-Temperature Prediction Interpretable Researchers have found a simple and robust scheme for interpreting the output of a sophisticated data-driven approach that predicts the Curie temperature (TC) of a binary alloy consisting of transition metals and rare-earth elements by measuring the correlation among descriptors. Curie temperature ; Marie curie ; Curie ; Binary number ; Simple (philosophy) ; Alloy ; Materials science ; Rare earth ; Statistical physics ; Condensed matter physics ; Curie–Weiss law ; Curie's law ; Thermodynamics ; Data mining ; Mathematics ; Computer science ; Physics ; Ferromagnetism ; Metallurgy ; Philosophy Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Iron-based superconductors research
Authors: " | Ștefănuț Ciochină | Dunarea de Jos" | Mirela Praisler
Source: Annals of the ”Dunarea de Jos” University of Galati Fascicle II Mathematics Physics Theoretical Mechanics (article, 2018-06-10)
Field: Chemistry — Analytical Chemistry

"Naive Bayesian classifier detecting phenethylamines based on their vibrational spectra and associated eigenvalues " In this paper we are presenting an artificial intelligence application designed to screen for controlled phenethylamines. The training set consists of 30 vibrational spectra of stimulant and hallucinogenic amphetamines, as well as of negatives (non-amphetamines representing randomly selected chemicals of forensic interest). The Naive Bayesian Classifier indicates the likelihood that a substance belongs to one of the predefined classes. For this aim, in our case, the Principal Component Analysis (PCA) scores of the targeted compounds are subjected to a Naive Bayesian Classifier. The advantages of combining these two pattern recognition methods over the use of each method independently are discussed from the point of view of the detection efficiency. Principal component analysis ; Bayesian probability ; Artificial intelligence ; Pattern recognition (psychology) ; Phenethylamines ; Classifier (UML) ; Naive Bayes classifier ; Computer science ; Machine learning ; Mathematics ; Chemistry ; Stereochemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Zhenbin Wang
Source: eScholarship (California Digital Library) (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Design and Optimization of Phosphors for Solid-State Lighting using First-Principles Calculations The discovery of novel phosphors is key to the development of highly efficient and environmental friendly light-emitting diodes (LED)-based solid-state lighting. This discovery, however, has largely taken place through painstaking experiments in an Edisonian fashion. In this thesis, we use first-principles calculations to explore new phosphor materials and advance our understanding of photoluminescence (PL) properties. Phosphors with narrow-band emission are a critical component for high brightness LEDs and liquid crystal display (LCD) backlighting with wide color gamut. In the first part, we discovered a quantitative descriptor for narrow-band Eu2+-activated emission by comparing electronic structures of known narrow-band and broad-band phosphors. Incorporating this descriptor into a high throughput first principles screening of 2,259 nitride compounds, we identified five promising new nitride hosts for Eu2+-activated red-emitting phosphors that are predicted to exhibit good chemical stability, thermal quenching resistance and quantum efficiency, as well as narrow-band emission. In the second part, we performed a systematic investigation of structure-composition-property relationships in Eu2+-activated Î²-SiAlON, one of the most promising narrow-band green phosphors. Using first-principles calculations, we first identified the most energetically favorable structure for Î²-SiAlON:Eu2+ and then studied the effect of oxygen content and Eu2+ activator concentrations on the local EuN9 activator environment, and its impact on important PL properties such as emission peak position, bandwidth, and thermal quenching resistance. The insights obtained provide a constructive means to optimize the PL performance of Î²-SiAlON in experiment. In the third part, we developed an approach to discover new oxide phosphors by mining unexplored chemistries with data-driven structure prediction and high-throughput screening. This approach was demonstrated by the prediction and experimental validation of a novel, earth-abundant Eu2+ and Ce3+-activated Sr2LiAlO4 phosphors. The Sr2LiAlO4:Eu2+/Ce3+ phosphors exhibit broad emissions at Î»max ~ 512 nm (green-yellow) and Î»max ~ 434 nm (blue), respectively, with excellent thermal quenching resistance of &gt; 88% intensity at 150 C. A prototype white LED utilizing Sr2LiAlO4-based phosphors yields an excellent color rendering index exceeding 90. Phosphor ; Backlight ; Sialon ; Light-emitting diode ; Photoluminescence ; Optoelectronics ; Materials science ; Solid-state lighting ; Brightness ; Band gap ; Activator (genetics) ; Nanotechnology ; Chemistry ; Liquid-crystal display ; Optics ; Ceramic ; Physics Luminescence Properties of Advanced Materials ; Inorganic Chemistry and Materials ; Gas Sensing Nanomaterials and Sensors
Authors: V. Dovgalyuk
Source: Modern technology materials and design in construction (article, 2018-03-06)
Field: Chemistry — Spectroscopy

CONCEPTUAL BASIS OF THE ANALYSIS OF HEAT-AND MASS-TRANSFER IN LAYERED CAPILLARY-PORRATED TISSES &nbsp;The phenomena of contact heat and mass transfer between materials of different physical and chemical structures are quite widespread in the technological processes of various industries, which leads to the need for further studies of their kinetics, for example, when drying capillary-porous bodies. It has been established that many researchers studied non-stationary problems of heat and mass exchange of a piecewise-homogeneous unbounded two-layered plate with the surrounding medium, but some details of these processes have not yet been established. The authors of the paper give an analytical solution of the non-stationary problem of heat and mass conductivity of a piecewise homogeneous unbounded double-layered plate, which, with one surface, takes part in convective heat and mass transfer with the surrounding medium with constant potentials of heat and mass transfer, while the other surface is heat and moisture-insulated . This model adequately describes the processes of heat and mass exchange in a canvas, exhibited in the museum's premises, to which the flow of visitors moves. The first layer simulates the paints that are applied of the picture, and the second one – directly the basis of the painting (the art painting itself). As a result of the solution of the problem by mathematical physics, the influence of individual heat and mass transfer criteria on heat and mass transfer in this plate is established. The results obtained by the authors can be used to specify and improve the existing engineering methods for calculating the parameters of nonstationary heat and mass transfer in layered capillary-porous bodies, as well as to develop more advanced algorithms for controlling the artificial microclimate of museum premises on the basis of modern information technologies and fuzzy logic controllers / controllers, as in the stages of designing (constructing) artificial intelligence systems for the management of the climate of museum premises, and in their real modes their operation. Capillary action ; Mass transfer ; Basis (linear algebra) ; Mechanics ; Thermodynamics ; Physics ; Mathematics ; Geometry Aerogels and thermal insulation ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry ; Gas Dynamics and Kinetic Theory
Authors: Ivan Trapić | Robert Pezer | Jurica Sorić
Source: Transactions of FAMENA (article, 2018-10-19)
Field: Materials Science — Materials Chemistry

Atomistic Modelling of 2D Stress Distribution Around Discontinuities Molecular dynamics simulations have been used for decades to investigate continuum mechanics failure to give the correct distribution of stress near discontinuities, such as holes and crack tips. In this paper, stress distribution around elliptical holes in a sheet material has been examined in an atomistic and a continuum model. Atomistic interactions are described by the Tersoff potential tuned for carbon. Calculations were conducted for the problem of stress distribution around the elliptic hole in a 2D graphene sheet subjected to the gradually increasing uniaxial tension load. The atomistic stress is calculated as spatial average utilizing Hardy's formulation. The results have been compared with the Kirsch solution for stress concentration at the edge of the circular hole. A quantitative measure for switching from atomistic to continuum model and vice versa has been proposed. Routes toward the effective data-driven coupling of macro-and micromechanical models where continuum mechanics approach fails are pointed out. Classification of discontinuities ; Materials science ; Stress (linguistics) ; Mathematics ; Mathematical analysis Microstructure and mechanical properties ; Graphene research and applications ; Ion-surface interactions and analysis