jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ayaz Mahmood Dar
Source: Organic and Medicinal Chemistry International Journal (article, 2018-10-09)
Field: Chemistry — Organic Chemistry

Synthesis, Characterization and Cytotoxic Studies of New Thiazolidinones Juniper Publishers is a platform for professors and researchers who aspire to give out quality information based on their research and expertise, in an attempt to aid scholars/researchers in their field of interest. We, as Open Access publishers, strive to offer the best in class online science publications Chemistry ; Steric effects ; Moiety ; Acetophenone ; Hydrazone ; Hydrazine (antidepressant) ; Stereochemistry ; Acetic acid ; Carbon-13 NMR ; Medicinal chemistry ; Organic chemistry Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and Reactivity of Sulfur-Containing Compounds
Authors: Ran Adler | Chang‐Jong Kang | Chuck-Hou Yee | Gabriel Kotliar
Source: Reports on Progress in Physics (article, 2018-08-23)
Field: Materials Science — Materials Chemistry

Correlated materials design: prospects and challenges The design of correlated materials challenges researchers to combine the maturing, high throughput framework of DFT-based materials design with the rapidly-developing first-principles theory for correlated electron systems. We review the field of correlated materials, distinguishing two broad classes of correlation effects, static and dynamics, and describe methodologies to take them into account. We introduce a material design workflow, and illustrate it via examples in several materials classes, including superconductors, charge ordering materials and systems near an electronically driven metal to insulator transition, highlighting the interplay between theory and experiment with a view towards finding new materials. We review the statistical formulation of the errors of currently available methods to estimate formation energies. We formulate an approach for estimating a lower-bound for the probability of a new compound to form. Correlation effects have to be considered in all the material design steps. These include bridging between structure and property, obtaining the correct structure and predicting material stability. We introduce a post-processing strategy to take them into account. Bridging (networking) ; Computer science ; Material Design ; Workflow ; Stability (learning theory) ; Statistical physics ; Nanotechnology ; Materials science ; Physics ; Machine learning Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Superconductivity in MgB2 and Alloys
Authors: Letif Mones | Christoph Ortner | Gábor Cśanyi
Source: Scientific Reports (preprint, 2018-09-12)
Field: Chemistry — Physical and Theoretical Chemistry

Preconditioners for the geometry optimisation and saddle point search of molecular systems A class of preconditioners is introduced to enhance geometry optimisation and transition state search of molecular systems. We start from the Hessian of molecular mechanical terms, decompose it and retain only its positive definite part to construct a sparse preconditioner matrix. The construction requires only the computation of the gradient of the corresponding molecular mechanical terms that are already available in popular force field software packages. For molecular crystals, the preconditioner can be combined straightforwardly with the exponential preconditioner recently introduced for periodic systems. The efficiency is demonstrated on several systems using empirical, semiempirical and ab initio potential energy surfaces. Preconditioner ; Hessian matrix ; Saddle point ; Energy minimization ; Exponential function ; Ab initio ; Computation ; Point (geometry) ; Matrix (chemical analysis) ; Computer science ; Mathematics ; Computational science ; Computational chemistry ; Geometry ; Applied mathematics ; Physics ; Algorithm ; Materials science ; Chemistry ; Mathematical analysis ; Iterative method ; Quantum mechanics Crystallography and molecular interactions ; Advanced Chemical Physics Studies ; Advanced NMR Techniques and Applications
Authors: Nils Jansen | Joost-Pieter Katoen | Pusmeet Kohli | Jan Křetínský
Source: DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) (article, 2018-01-01)
Field: Chemistry — Spectroscopy

Machine Learning and Model Checking Join Forces (Dagstuhl Seminar 18121) This report documents the program and the outcomes of Dagstuhl Seminar 18121 "Machine Learning and Model Checking Join Forces". This Dagstuhl Seminar brought together researchers working in the fields of machine learning and model checking. It helped to identify new research topics on the one hand and to help with current problems on the other hand. Join (topology) ; Computer science ; Model checking ; Programming language ; Artificial intelligence ; Mathematics Advanced Proteomics Techniques and Applications ; Statistical and Computational Modeling
Authors: Truong Ka My Dang
Source: mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (article, 2018-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Microwire arrays for studying the influence of temperature gradients on the cellular behavior Temperature plays an important role in regulating the biological function of cellular development. Over the past few decades, the development of microfabrication technology has enabled highly localized temperature control at the scale of a few microns. This allows the study of thermal influences on biological microsystems. In this context, the present thesis investigates the changes of cellular behavior depending on temperature gradients using microwire arrays. Microfabrication ; Context (archaeology) ; Nanotechnology ; Temperature gradient ; Materials science ; Thermal ; Function (biology) ; Microsystem ; Temperature control ; Scale (ratio) ; Biological system ; Mechanical engineering ; Engineering ; Physics ; Biology ; Cell biology thermodynamics and calorimetric analyses ; 3D Printing in Biomedical Research ; Neuroscience and Neural Engineering
Authors: Gabriella Elisa Silva Nogueira | Karina Heck da Silva | Adelir Aparecida Saczk | André Ribeiro
Source: Revista Eletrônica de Gestão e Tecnologias Ambientais (article, 2018-04-24)
Field: Chemistry — Inorganic Chemistry

A GERAÇÃO DE RESÍDUOS SÓLIDOS POR CURTUMES E ALTERNATIVAS DE TRATAMENTO E REÚSO &lt;p&gt;As atividades industriais geram resíduos de formas variadas que, predominantemente, apresentam um elevado grau de poluição, tendo, na maioria das vezes, os aterros industriais como disposição final. A indústria do couro é uma grande geradora de resíduos industriais, os quais apresentam volume residual da pele e de cromo, do couro curtido e do tratamento dos efluentes gerados durante a produção. Aterrar resíduos de curtume, além de um potencial risco de contaminação ambiental, gera gastos e resulta em desperdício de material potencialmente reaproveitável. Diante da necessidade de alerta e alternativas ao aterramento desses resíduos, tratamentos para a remoção do cromo, através de processos físico-químicos e biológicos, são indicados para o reaproveitamento do material. O objetivo deste trabalho foi revisar a literatura científica em busca das informações consagradas sobre as diferentes metodologias aplicadas na recuperação do resíduo. Há uma inclinação pela adoção de técnicas que removem o cromo de efluentes e do lodo de curtume para seu melhor reaproveitamento e incorporação em diversos setores produtivos.&lt;/p&gt; Physics ; Chemistry Pigment Synthesis and Properties ; Chromium effects and bioremediation ; Recycling and Waste Management Techniques
Authors: Nudrat Humera | Hadia Noor | Saira Riaz | Shahzad Naseem
Source: Key engineering materials (article, 2018-09-05)
Field: Materials Science — Materials Chemistry

Analysis of Electric Transport Mechanism of Barium Titanate by Impedance Spectroscopy Barium titanate (BTO) samples were prepared by nanomilling based solid state reaction method. Dielectric behavior of BTO sample has been investigated by temperature dependent impedance spectroscopy. The impedance analysis of BTO samples confirm that hopping of electrons and defects coexisted in sample and contribution of grain and grain boundary to dielectric behavior is discussed. A single semicircular arc obtained by Nyquist plots whose radius decreased with increase in temperature illustrates the prominent role of grains. The activation energy of defects was calculated from Arrhenius plot. These defects may be due to oxygen vacancies and hopping between Ti +4 to Ti +3 ions. Barium titanate ; Dielectric spectroscopy ; Materials science ; Arrhenius plot ; Grain boundary ; Nyquist plot ; Activation energy ; Dielectric ; Arrhenius equation ; Analytical Chemistry (journal) ; Spectroscopy ; Condensed matter physics ; Composite material ; Chemistry ; Electrode ; Microstructure ; Physical chemistry ; Optoelectronics ; Electrochemistry Ferroelectric and Piezoelectric Materials ; Dielectric properties of ceramics ; Microwave Dielectric Ceramics Synthesis
Authors: Gabor Nagy | Maxim Igaev | Søren V. Hoffmann | Nykola C. Jones | Helmut Grubmüller
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-03-09)
Field: Chemistry — Spectroscopy

SESCA: Predicting Circular Dichroism Spectra from Protein Molecular Structures Abstract Circular dichroism spectroscopy is a highly sensitive, but low-resolution technique to study the structure of proteins. Combined with molecular modelling or other complementary techniques, CD spectroscopy can provide essential information at higher resolution. To this end, we introduce a new computational method to calculate the electronic circular dichroism spectra of proteins from a structural model or ensemble using the average secondary structure composition and a pre-calculated set of basis spectra. We compared the predictive power of our method to existing algorithms – namely DichroCalc and PDB2CD – and found that it predicts CD spectra more accurately, with a 50% smaller average deviation from the measured CD spectra. Our results indicate that the derived basis sets are robust to experimental errors in the reference spectra and to the choice of the secondary structure classification algorithm. For over 80% of the globular reference proteins, our basis sets accurately predict the experimental spectrum solely from their secondary structure composition. For the remaining 20%, correcting for intensity normalization considerably improves the prediction power. Additionally, we show that the predictions for short peptides and intrinsically disordered proteins strongly benefit from accounting for side-chain contributions and structural flexibility. Table Of Content Graphics: Circular dichroism ; Spectral line ; Globular protein ; Protein secondary structure ; Spectroscopy ; Basis (linear algebra) ; Normalization (sociology) ; Protein structure Molecular spectroscopy and chirality ; Protein Structure and Dynamics ; Machine Learning in Bioinformatics
Authors: Reza Farahmandfar | Maryam Asnaashari | Reza Esmaeilzadeh Kenari | E Desmond | V Kemi | M Krkkinen | C Lamberg-Allardt | S Mexis | E Chouliara | M Kontominas | K Sallam | M Cowan | Y Amakura | Y Umino | S Tsuji | H Ito | T Hatano | T Yoshida | Y Tonogai | M Asnaashari | R Farhoosh | A Sharif | R Farahmandfar | R Sayyad | S Khanzadi | S Gharibzadeh | M Raoufy | V Razavilar | R Khaksar | B Radmehr | M Abdollahi | M Rezaei | G Farzi | Y Jiang | N Wu | Y.-J Fu | W Wang | M Luo | C.-J Zhao | Y.-G Zu | X.-L Liu | O Politeo | M Jukic | M Milos | P Tongnuanchan | S Benjakul | T Prodpran | S Pisuchpen | K Osako | M Vinatoru | D Velikovi | D Milenovi | M Risti | V Veljkovi | A Kimbaris | N Siatis | C Pappas | P Tarantilis | D Daferera | M Polissiou | S Albu | E Joyce | L Paniwnyk | J Lorimer | T Mason | A Goulas | T Misharina | A Polshkov | S Manju | L Jose | T Gopal | C Ravishankar | K Lalitha | S Aubourg | F Prez-Alonso | J Gallardo | M Zolfaghari | B Shabanpour | S Falahzadeh
Source:  (article, 2018-08-06)
Field: Chemistry — Organic Chemistry

Effect of Rosmarinus officinalis and Ocimum basilicum Extract on Peroxide Value, Carbonyl Compound, and Free Fatty Acids of Fish Oil One of the newest attended techniques is ultrasound-assisted extraction. This method is more efficient and economic than solvent and ultrasound apart from. The purpose of the present work was evaluated and compare Rosmarinus officinalis and Ocimum basilicum extraction on the quality of fish oil in similar conditions. Results of chemical tests (peroxide value, carbonyl compound, and free fatty acids) showed that both of extracts could increase the storage period of Hypophthalmichtys molitrix fish oil. They delayed production of undesirable metabolites in samples and Rosmarinus officinalis extract was better than Ocimum basilicum one. In agreement, higher concentrations of both extracts were better than lower ones. There were significant differences between control and treated samples. This technique could be replaced for extraction from different sources. Rosmarinus ; Basilicum ; Ocimum ; Officinalis ; Peroxide value ; Chemistry ; Fish oil ; Food science ; Organic chemistry ; Fish <Actinopterygii> ; Essential oil ; Botany ; Biology ; Fishery Edible Oils Quality and Analysis ; Essential Oils and Antimicrobial Activity ; Psidium guajava Extracts and Applications
Authors: Amine Riad | Mohamed Mansouri
Source: Preprints.org (preprint, 2018-12-13)
Field: Materials Science — Materials Chemistry

Radiation Effect on Shape Memory Alloy The shape memory alloys belong to the smart materials thanks to their thermomechanical proprieties' reply to thermal or to mechanical loading. These materials can change shape, stiffness, displacement, natural frequency, and many mechanical characteristics in response to stress or to heat such as conduction, convection or radiation. However, heating by convection or conduction are the most useful and studied methods unlike radiation. Therefore, this paper aims to study the radiation effect on the shape memory alloy behavior Shape-memory alloy ; Thermal conduction ; Materials science ; Radiation ; Convection ; Thermal radiation ; Displacement (psychology) ; Alloy ; Stiffness ; Natural convection ; Thermal ; Stress (linguistics) ; Composite material ; Mechanics ; Optics ; Thermodynamics ; Physics Shape Memory Alloy Transformations
Authors: В. Н. Скоробогатых | Nikolay Petrovich Anosov | П. А. Козлов | Lyubov Yu. Gordyuk | A. S. Gudenko | A. Korneev | E. M. Simich-Lafitskaya | E. V. Pogorelov
Source: KnE Materials Science (article, 2018-05-06)
Field: Materials Science — Metals and Alloys

Studies of the Chemical and Structural Heterogeneity of the Technological Model of the Fusion Boundary of Pearlitic Steel and the Material of the Anticorrosive Cladding of VVER . Materials science ; Cladding (metalworking) ; Fusion ; VVER ; Metallurgy ; Composite material ; Nuclear engineering ; Engineering Hydrogen embrittlement and corrosion behaviors in metals ; Welding Techniques and Residual Stresses ; Fusion materials and technologies
Authors: Canhui Wang | Wei‐Chang Yang | Devika Sil | Amit Agrawal | Renu Sharma
Source: Microscopy and Microanalysis (article, 2018-08-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Engineering the Energy Flow in Nanoparticles for Plasmonically Enhanced Catalysis An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button. Nanoparticle ; Flow (mathematics) ; Nanotechnology ; Materials science ; Action (physics) ; Computer science ; Mechanics ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Electrocatalysts for Energy Conversion ; Advanced Photocatalysis Techniques
Authors: Mauricio Araya | Marcelo Mendoza | Mauricio Solar | Diego Mardones | A. Bayo
Source: Astronomy and Computing (article, 2018-06-15)
Field: Chemistry — Analytical Chemistry

Unsupervised learning of structure in spectroscopic cubes Computer science ; Cluster analysis ; Unsupervised learning ; Dimensionality reduction ; Artificial intelligence ; Context (archaeology) ; Big data ; Algorithm ; Heuristic ; Set (abstract data type) ; Pattern recognition (psychology) ; Data mining ; Machine learning Spectroscopy and Chemometric Analyses ; Spectroscopy and Laser Applications ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Xinli Li | Yijiao Li | Gang Lü | Yong Yan
Source: Kent Academic Repository (University of Kent) (article, 2018-08-13)
Field: Chemistry — Analytical Chemistry

Biomass Fuel Identification Based on Flame Spectroscopy and Feature Engineering Flame spectra contain useful information about combustion and hence the spectral features of flame radicals may be used to identify different biomass fuels. A technique for biomass fuel identification is proposed based on the spectral features of flame radicals, feature engineering and improved support vector machine. The spectral intensity signals of biomass flames and flame radicals (OH*(310.85nm), CN*(390.00nm), CH*(430.57nm) and C2*(515.23nm, 545.59nm)) were acquired using a spectrometer. Feature engineering was built, which can accurately reflect the characteristics of sample category, through feature extraction, feature selection based on Filter and feature learning based on dictionary learning. The support vector machine is used to build the identification model, where radial basis kernel parameter ? and error penalty factor C are optimized using an improved grid search algorithm. Experimental results from a laboratory-scale combustion rig show the effectiveness of the proposed method for the identification of biomass fuel. Combustion ; Support vector machine ; Feature (linguistics) ; Biomass (ecology) ; Pattern recognition (psychology) ; Spectrometer ; Feature selection ; Feature extraction ; Artificial intelligence ; Computer science ; Chemistry ; Optics ; Physics ; Organic chemistry Spectroscopy and Chemometric Analyses ; Advanced Algorithms and Applications ; Industrial Technology and Control Systems
Authors: KOH Leng-Duei
Source: Annals of Biotechnology (article, 2018-08-30)
Field: Materials Science — Polymers and Plastics

The Future of ‘Self-Healing’ Technologies Recent years have witnessed significant advancement in 'self-healing' technologies. This is unlike a decade back, when 'self-healing' materials which are capable of restoring functionalities such as electrical conductivity or even optical (e.g., display) property after mechanical damage were practically non-existent. This editorial provides a quick introduction on reported 'self-healing' technologies, particularly those with rapid healing time and impressive restoration of functionalities (e.g., up to 90%). There is also an emphasis on the utilities and benefits of 'self-healing' technologies, as well as some of the key challenges in their integration and translation. It is anticipated that, with continued development and seamless integration of 'self-healing' materials into modern-day settings, it is set to open up a new era of enhanced consumer experience, infrastructure maintenance, environmental management, as well as countless unprecedented and unique applications resembling those in science fictions. Self-healing ; Emerging technologies ; Computer science ; Medicine ; Artificial intelligence ; Alternative medicine Polymer composites and self-healing ; Modular Robots and Swarm Intelligence ; Smart Materials for Construction
Authors: Temel Varol
Source: Pamukkale University Journal of Engineering Sciences (article, 2018-01-01)
Field: Materials Science — Ceramics and Composites

The effect of Milling time, Milling Speed and Ball to Powder Weight Ratio on the Physical Properties of Submicron Al2O3 Ceramic Particles Fabricated by Mechanical milling Method Bu çalışmada mekanik öğütme yöntemi ile kaba toz boyutuna sahip Al2O3 (Alüminyum Oksit) tozlarından mikronaltı ve nano toz boyutuna sahip Al2O3 tozlarının üretimi amaçlanmıştır. Aynı zamanda mekanik öğütme işlemine tabi tutulan Al2O3 tozlarının morfolojisi, parçacık boyutu, özgül yüzey alanı, görünür yoğunluğu ve mikroyapısı üzerine mekanik öğütme parametreleri olan öğütme zamanı, öğütme hızı ve bilye toz ağırlık oranının etkisi araştırılmıştır Ball mill ; Materials science ; Ceramic ; Ball (mathematics) ; Composite material ; Metallurgy ; Geometry ; Mathematics Advanced ceramic materials synthesis ; Additive Manufacturing and 3D Printing Technologies ; Material Selection and Properties
Authors: Amandeep Kaur and Monika Gupta
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2018-08-01)
Field: Materials Science — Polymers and Plastics

Development And Validation Of Method By Hplc Techniques <em>The primary focus of the review article is on general approaches and considerations toward development of chromatographic methods for separation, identification, and quantification of compounds, which may be applied within the various functions in the drug development continuum. This article also discusses the issues and parameters that must be considered in the validation of analytical methods. At the end of the review, a scope of the present research study is covered.</em> <strong>Keywords: </strong><em>Introduction, Method development, Steps for HPLC method development, Method validation, Advantages of method validation and Parameters for validation. </em> Computer science ; Environmental science Synthesis and properties of polymers
Authors: J. Li | C. F. Zhang | Rui Yin | Wuju Zhang
Source: Hrčak Portal of scientific journals of Croatia (University Computing Centre) (article, 2018-10-01)
Field: Materials Science — Ceramics and Composites

Prediction of mechanical properties of β-SiAlON ceramics based on BP neural network -Si 6-Z Al Z O Z N 8-Z (0<Z2) ceramics with rod-like grain morphology were prepared by gas pressure sintering, and their mechanical properties (i.e., bulk density, hardness, fracture toughness, and flexural strength) were evaluated.A model to predict the mechanical properties of -SiAlON ceramics was established by back propagation (BP) neural network, and the relationships between process parameters (i.e., Z-value and temperature) and mechanical properties were investigated.Results show that the model had good prediction accuracy and maximum relative error lower than 8 %.The model could reflect the complex nonlinear relationship between the process parameters and the mechanical properties of -SiAlON ceramics.The model can provide an effective reference for optimizing the design of -SiAlON ceramics. Sialon ; Artificial neural network ; Materials science ; Ceramic ; Composite material ; Metallurgy ; Computer science ; Artificial intelligence Advanced ceramic materials synthesis