jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: М. В. Киричков | Aram L. Bugaev | Alina Skorynina | Vera V. Butova | Andriy P. Budnyk | Alexander A. Guda | Alexander L. Trigub | А. В. Солдатов
Source: Metals (article, 2020-06-17)
Field: Chemistry — Inorganic Chemistry

In Situ Time-Resolved Decomposition of β-Hydride Phase in Palladium Nanoparticles Coated with Metal-Organic Framework The formation of palladium hydrides is a well-known phenomenon, observed for both bulk and nanosized samples. The kinetics of hydrogen adsorption/desorption strongly depends on the particle size and shape, as well as the type of support and/or coating of the particles. In addition, the structural properties of hydride phases and their distribution also depend on the particle size. In this work, we report on the in situ characterization of palladium nanocubes coated with HKUST-1 metal-organic framework (Pd@HKUST-1) during desorption of hydrogen by means of synchrotron-based time-resolved X-ray powder diffraction. A slower hydrogen desorption, compared to smaller sized Pd nanoparticles was observed. Rietveld refinement of the time-resolved data revealed the remarkable stability of the lattice parameters of α- and β-hydride phases of palladium during the α- to β- phase transition, denoting the behavior more similar to the bulk materials than nanoparticles. The stability in the crystal sizes for both α- and β-hydride phases during the phase transition indicates that no sub-domains are formed within a single particle during the phase transition. Palladium hydride ; Palladium ; Hydride ; Materials science ; Desorption ; Hydrogen storage ; Hydrogen ; Synchrotron ; Nanoparticle ; Chemical engineering ; Particle size ; Rietveld refinement ; Transition metal ; Inorganic chemistry ; Adsorption ; Crystallography ; Physical chemistry ; Metal ; Chemistry ; Crystal structure ; Nanotechnology ; Catalysis ; Metallurgy ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; X-ray Diffraction in Crystallography
Authors: Yuliia Orlova
Source: UvA-DARE (University of Amsterdam) (article, 2020-01-01)
Field: Chemistry — Spectroscopy

Graph-theoretical approach to algorithmic construction of complex reaction networks Many processes that occur in nature feature complex reaction networks, such as natural oils and resins, and metabolic oxidation reactions. The challenge of studying such system originates in the heterogeneity of the reaction pathways occurring in the material as well as in the growth of the molecules to intractable sizes. In this thesis, a multi-scale modeling methodology based on formal language approach is proposed to describe the chemical system from atomistic level to the level of large polymers molecules. The methodology consists of automatic reconstruction of a finite reaction network describing polymerizing system, solution of the kinetic model providing concentration profiles of various functional groups and crosslinks, and extraction of global properties of a polymer network using findings from random graph theory. Chapter 2 offers a thorough description of the modeling methodology and its modification to include polymer structures. Chapter 3 offers a comprehensive survey on chemistry of linseed oil, which is a bio-based polymer used as an application of our methodology. In Chapter 4, modeling methodology is used to uncover the autoxidation reaction scheme of triolein and to interpret ESI-MS measurements of aged triolein samples. In Chapter 5 the methodology is applied to reconstruct and solve the kinetic model describing drying and degradation of ethyl linoleate (EL), as a model system of linseed oil. Using this application, we draw a parallel between chemistry and language using Chmosky's idea of formal grammar. Computer science ; Triolein ; Complex system ; Linseed oil ; Graph ; Polymer ; Complex network ; Theoretical computer science ; Chemistry ; Biological system ; Biochemical engineering ; Artificial intelligence ; Organic chemistry Analytical Chemistry and Chromatography
Authors: Irni Hamiza Hamzah | Azman Ab Malik | Aida Zulia Zulhanip | Zainal Hisham Che Soh | Alhan Farhanah Abd Rahim
Source: Indonesian Journal of Electrical Engineering and Computer Science (article, 2020-02-09)
Field: Chemistry — Electrochemistry

Cyclic voltammetry characterization analysis on the cu/flame retardant 4 fabricated biosensor Silicon, glass and ceramic are commonly base substrate used in DNA biosensor fabrication due to its biocompatible, expensive, hard and brittle. However due to the difficulty for drilling and dicing, these materials required expensive equipments and complex methodology of fabrication. Large gap of thermal expansion coefficient (TEC) between silicon/glass and film caused microcracks. Hence, the aim of this work is to investigate the suitability and the application of a non-biocompatible material, flame retardant 4 (FR4) as a base substrate for a label free DNA biosensor. Cyclic voltammetry (CV) reversible method has been implemented to test the fabricated Cu/Au on the FR4. It is found that the fabrication of Au has been made possible by the used of oxide-free Cu as an adhesion layer on the FR4 substrate. The area size of counter electrode (CE), working electrode (WE) and reference electrode (RE) are found to be 6.25 mm&lt;sup&gt;2&lt;/sup&gt;, 0.581 mm&lt;sup&gt;2&lt;/sup&gt; and 1.04 mm&lt;sup&gt;2&lt;/sup&gt;, respectively, in order to achieve the unity reversible redox relationship and to ensure the sensor’s reliability for 10 mM K3Fe(CN)6 solution in 0.1 M KCl. Thus it can be concluded that the proposed FR4-based substrate fulfilled the CV reversible process characterization. Materials science ; Substrate (aquarium) ; Wafer dicing ; Biosensor ; Fabrication ; Cyclic voltammetry ; Silicon ; Electrode ; Composite material ; Nanotechnology ; Analytical Chemistry (journal) ; Layer (electronics) ; Chemical engineering ; Optoelectronics ; Electrochemistry ; Chemistry ; Chromatography Electrochemical Analysis and Applications ; Molecular Junctions and Nanostructures ; Analytical Chemistry and Sensors
Authors: Magnus Fant | Mattias Ångqvist | Anders Hellman | Paul Erhart
Source: Angewandte Chemie (article, 2020-12-14)
Field: Chemistry — Inorganic Chemistry

To Every Rule There is an Exception: A Rational Extension of Loewenstein's Rule Abstract Loewenstein's rule, which states that Al−O−Al motifs are energetically unstable, is fundamental to the understanding and design of zeolites. Here, using a combination of electronic structure calculations and lattice models, we show under which circumstances this rule becomes invalid and how it can be rationally extended using the chabasite framework for demonstration. Extension (predicate logic) ; Lattice (music) ; Sum rule in quantum mechanics ; Computational chemistry ; Electronic structure ; Theoretical physics ; Chemistry ; Statistical physics ; Computer science ; Physics ; Quantum mechanics ; Programming language Zeolite Catalysis and Synthesis ; Machine Learning in Materials Science ; Advanced Chemical Physics Studies
Authors: Md Imdadul Islam | Fengyuan Lu
Source:  (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Mechanical properties of thermally stable cadmium iodoapatite ceramic by reactive spark plasma sintering technique Apatites based materials have been considered as potential waste forms to immobilize the long-lived radioactive iodine isotope. But the thermal instability and phase decomposition at a higher temperature hamper the waste management process. Spark plasma sintering can be a suitable technique compared to conventional sintering processes due to its rapid heating rate, lower sintering temperature and holding time. In this study, we synthesized a highly dense iodine bearing cadmium iodoapatite ceramic pellets by spark plasma sintering (SPS) technique. We successfully consolidated iodoapatite pellets with ~95.5% of theoretical density (TD) without any iodine loss and phase decomposition after low temperature sintering at 350 o C for 15 mins under 100 MPa. The theoretical density, micro-hardness, and yield strength of sintered pellets were investigated for different sintering temperatures of 300 o C, 350 o C, and 400 o C and holding time (15 min) under the pressure of 100 MPa. The densified pellets displayed nanocrystalline grain structures of 30-80 nm size which contributed to enhanced thermal stability and fracture toughness. The X-ray diffraction and EDS analysis also confirms the presence of iodoapatite structures. This advanced fabrication technique using SPS can help to develop thermally durable waste forms and mitigate the challenges to dispose high-level radioactive waste. Spark plasma sintering ; Materials science ; Ceramic ; Plasma ; SPARK (programming language) ; Sintering ; Composite material ; Metallurgy ; Computer science Nuclear materials and radiation effects ; Advanced ceramic materials synthesis ; Microwave Dielectric Ceramics Synthesis
Authors: Liwei Cao | Mikhail Kabeshov | Steve Ley | Alexei A. Lapkin
Source: ChemRxiv (preprint, 2020-03-10)
Field: Chemistry — Inorganic Chemistry

In Silico Rationalisation of Selectivity and Reactivity in Pd-Catalysed C-H Activation Reactions &lt;p&gt;A computational approach has been developed to automatically generate and analyse the structures of the intermediates of palladium catalysed carbon-hydrogen (C-H) activation reactions as well as to predict the final products. Implemented as a high-performance computing cluster tool, it has been shown to correctly choose the mechanism and rationalise regioselectivity of chosen examples from open literature reports. The developed methodology is capable of predicting reactivity of various substrates by differentiation between two major mechanisms - proton abstraction and the electrophilic aromatic substitution. An attempt has been made to predict new C-H activation reactions. This methodology can also be used for the automated reaction planning, as well as a starting point for microkinetic modelling.&lt;/p&gt; Regioselectivity ; Reactivity (psychology) ; Chemistry ; Electrophile ; Combinatorial chemistry ; In silico ; Catalysis ; Palladium ; Selectivity ; Computational chemistry ; Hydrogen atom abstraction ; Hydrogen ; Computer science ; Stereochemistry ; Organic chemistry Asymmetric Hydrogenation and Catalysis ; Chemical Reactions and Isotopes ; Machine Learning in Materials Science
Authors: Amina Mollaysa | Brooks Paige | Alexandros Kalousis
Source: ArODES (HES-SO (https://www.hes-so.ch/)) (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Goal-directed generation of discrete structures with conditional generative models Despite recent advances, goal-directed generation of structured discrete data remains challenging. For problems such as program synthesis (generating source code) and materials design (generating molecules), finding examples which satisfy desired constraints or exhibit desired properties is difficult. In practice, expensive heuristic search or reinforcement learning algorithms are often employed. In this paper, we investigate the use of conditional generative models which directly attack this inverse problem, by modeling the distribution of discrete structures given properties of interest. Unfortunately, the maximum likelihood training of such models often fails with the samples from the generative model inadequately respecting the input properties. To address this, we introduce a novel approach to directly optimize a reinforcement learning objective, maximizing an expected reward. We avoid high-variance score-function estimators that would otherwise be required by sampling from an approximation to the normalized rewards, allowing simple Monte Carlo estimation of model gradients. We test our methodology on two tasks: generating molecules with user-defined properties and identifying short python expressions which evaluate to a given target value. In both cases, we find improvements over maximum likelihood estimation and other baselines. Computer science ; Python (programming language) ; Estimator ; Reinforcement learning ; Generative model ; Machine learning ; Generative grammar ; Heuristic ; Bridging (networking) ; Artificial intelligence ; Variance (accounting) ; Mathematical optimization ; Algorithm ; Mathematics ; Statistics Machine Learning in Materials Science ; Software Engineering Research ; Computational Drug Discovery Methods
Authors: Shaimaa Adnan | Rawaa Neamah
Source: International Journal of Pharmaceutical Quality Assurance (article, 2020-03-25)
Field: Chemistry — Organic Chemistry

Study the Biological Activity for Shiff Base and Β–Lactam Compounds that Synthesis and Identification from Pyrimidine Derivatives In This study We are synthesis and characterization of some Schiff base and β- lactam derivatives) by three steps. The First react 2-amino-4-Chloro-6-methyl pyrimidine with 4-amino acetophenone in an acid medium to get shiff base derivative(E)-4-(1-((4-Chloro-6-methyl pyridine-2-yl)imino)ethyl)aniline (1), the second step (1) react with (3,4-dimethoxybenzal dehyde,4-methyl benzaldehyde,4-dimethylamino benzaldehyde,4-bromo benzaldehyde,4–hydroxy benzaldehyde, 4-Nitro benzaldehyde) to get Schiff base derivatives (2-7), the last step (2-7) derivatives react with Chloro acetyl chloride to get –β-lactam derivatives.(8-13) All these compounds are characterization by Fourier Transform Infrared Spectroscopy (FTIR), (1 H-NMR),(13C- NMR). After that study, the biological activity for all these derivatives to word two kinds of bacteria study the Enzymatic and Cancer Cell. Benzaldehyde ; Chemistry ; Acetophenone ; Schiff base ; Aniline ; Pyrimidine ; Pyridine ; Organic chemistry ; Stereochemistry ; Catalysis Synthesis of β-Lactam Compounds ; Metal complexes synthesis and properties ; Inorganic and Organometallic Chemistry
Authors: Shin Kiyohara | Masashi Tsubaki | Teruyasu Mizoguchi
Source: Microscopy and Microanalysis (article, 2020-07-30)
Field: Materials Science — Materials Chemistry

Prediction of ELNES and Quantification of Structural Properties Using Artificial Neural Network 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. Artificial neural network ; Biological system ; Content (measure theory) ; Computer science ; Artificial intelligence ; Mathematics ; Biology Machine Learning in Materials Science ; Hydrogen embrittlement and corrosion behaviors in metals ; X-ray Diffraction in Crystallography
Authors: Calogero Giancarlo Piscopo | Angelos Polyzoidis | David Werner | Matthias Ahlhelm | Hans‐Jürgen Richter
Source: ChemistrySelect (article, 2020-09-03)
Field: Chemistry — Inorganic Chemistry

Breakthrough Screening of Porous Materials: A Simple and Effective Tool for Database Generation Abstract The release of toxic and noxious gases in the atmosphere has become a big concern, due to its adverse effect on the health and life quality in general. The development of efficient filter materials can help to tackle this issue, considering that the production of such gases in various processes cannot be prevented. Metal‐organic frameworks (MOFs) have emerged as a promising class of material to adsorb several toxic industrial chemicals (TICs). Nevertheless, identifying the suitable MOF material to adsorb a specific gas is a challenging task due to the lack of fast characterization methods. Using a mass spectrometer‐detector, a simple setup has been developed and applied to register breakthrough curves and evaluate the retention capacity of selected MOFs against NH 3 and H 2 S. The experimental results obtained using this in‐house assembled device are in agreement with several literature reports, resulting in a fast tool for the development of a gas adsorption database for porous materials. Additionally, for the specific case of Ni‐MOF‐74, the breakthrough measurements correlate well with the surface areas of the material, providing an additional and fast quality control method to evaluate the material synthesis. Adsorption ; Process engineering ; Characterization (materials science) ; Materials science ; Nanotechnology ; Porosity ; Environmental science ; Computer science ; Chemistry ; Engineering ; Composite material ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Mercury impact and mitigation studies ; Catalytic Processes in Materials Science
Authors: О.В. Пономаренко | S. Yu. Panshina | А Бакибаев | А Ташенов
Source: BULLETIN of the L N Gumilyov Eurasian National University Chemistry Geography Ecology Series (article, 2020-04-08)
Field: Chemistry — Organic Chemistry

Синтез и идентификация эфиров бициклических бисмочевин Современные тенденции развития органической химии предполагаютпоиск новых методов синтеза и исследований, способствующих более углубленномуи детальному изучению производных гетероциклических соединений. Бициклическиебисмочевины (родоначальником которых является гликолурил) выделяются высокойреакционной способностью и широкой областью практического применения. В статьепредставлен анализ методов синтеза эфиров на основе производного гликолурила –тетраметилолгликолурила, который находит применение как сшивающий агент при получениигликолурил-формальдегидных смол, а так же является стабилизатором красителей на воднойоснове. Подобранные методики позволяют синтезировать эфиры с оптимальным выходом, атакже использовать в реакциях спирты не только линейного, но и разветвленного строения.Свойства полученных соединений изучены методами ИК- и H 1, С 13 ЯМР спектроскопии. Chemistry Supramolecular Chemistry and Complexes ; Molecular Sensors and Ion Detection ; Crystallography and molecular interactions
Authors: Edgar A. Engel
Source: CrystEngComm (article, 2020-09-28)
Field: Materials Science — Materials Chemistry

Identification of synthesisable crystalline phases of water – a prototype for the challenges of computational materials design We discuss the identification of experimentally realisable crystalline phases of water to outline and contextualise some of the diverse building blocks of a computational materials design process. Identification (biology) ; Process engineering ; Materials science ; Computer science ; Nanotechnology ; Biochemical engineering ; Engineering Machine Learning in Materials Science ; Calcium Carbonate Crystallization and Inhibition ; High-pressure geophysics and materials
Authors: Ehsan Alimohammadi | Reza Maleki | Hossein Akbarialiabad | Mohammad Dahri
Source:  (preprint, 2020-10-12)
Field: Chemistry — Organic Chemistry

Atomistic insight into novel co-delivery of doxorubicin and paclitaxel using fullerene modified by dimethyl acrylamide trimethyl chitosan: A computational study <title>Abstract</title> <bold>Background</bold>: The distribution of drugs could not be controlled in the conventional drug delivery system. This has led to the development of a smart nanoparticle-based drug delivery system, known as smart drug delivery systems. In cancer research, novel biocompatible nanocarriers have received much attention for various ranges of anticancer drugs.In the current study, the effect of a novel co-polymer "dimethyl acrylamide-trimethyl chitosan" was investigated on drug delivery of doxorubicin and paclitaxel utilizing modified fullerene nanocarrier. This study was performed via molecular dynamics simulation based on acidic pH sensitivity of the cancer microenvironment. Furthermore, hydrogen bonds, diffusion coefficient, gyration radius, and drug-carrier interaction energies were investigated here. Interestingly, a simultaneous pH and temperature-sensitive system was proposed for paclitaxel and doxorubicin for a co-polymer. A pH-sensitive and temperature-sensitive copolymer was used based on trimethyl chitosan and dimethyl acrylamide, respectively. In such a dualistic approach, co-polymer makes an excellent option to have two properties in one bio-polymer. <bold>Results:</bold> The results suggest the dramatic and indisputable role of the co-polymer in the release of doxorubicin and paclitaxel in cancerous tissues, as well as an increased biocompatibility and drug uptake in a neutral state. The validation test was performed by repeated simulations of a similar article. The results are very close to those of the reference paper .<bold>Conclusions</bold>: Overall, conjugated fullerene and dimethyl acrylamide-trimethyl chitosan (DMAA-TMC) as carriers can be a good proposition for loading, delivery, and release of anti-cancer drugs based on a pH/temperature-sensitive smart drug delivery system. Acrylamide ; Chitosan ; Fullerene ; Paclitaxel ; Doxorubicin ; Chemistry ; Combinatorial chemistry ; Materials science ; Organic chemistry ; Medicine ; Polymer ; Chemotherapy Fullerene Chemistry and Applications ; Graphene and Nanomaterials Applications ; Polymer Nanocomposite Synthesis and Irradiation
Authors: Volodymyr Tkach | Marta V. Kushnir | Yana G. Ivanushko | Svitlana M. Lukanova | Sílvio C. De Oliveira | Petró Yagodynets
Source: Ukrainica Bioorganica Acta (article, 2020-06-30)
Field: Materials Science — Polymers and Plastics

The mathematical description of dopamine electrochemical oxidation, accompanied by its chemical and electrochemical polymerization The electrooxidation of dopamine is accompanied by its chemical and electrochemical polymerization, and in which either the monomer or the polymer may be oxidized to the respective quinonic form, was investigated from the theoretical point of view. Dopamine is one of the important neurotransmitters in human and mammal organisms. It is a precursor to epinephrine, which influences the cardiovascular, hormonal and renal functions. Its lack causes diseases like Parkinson, therefore, dopamine has been used as a drug for their treatment. On the other hand, its excess stimulates the sympatic nervous system yielding the metabolic disorders and even schizophrenia. Thus, the development of the rapid and accurate method for its concentration measurement is very important. Dopamine is very popular analyte in electroanalytical systems. The modified electrodes for its determinations have been developed by many researchers. Dopamine is widely used as a monomer for synthesis of a conducting polymer – polydopamine, whis is used as electrodes’ modifier in capacitors and in anticorrosive coatings. The electropolymerization of dopamine into polydopamine proceeds along with its traditional quinone-hydroquinonic oxidation. Both processes give their impact to the electrochemical behavior of dopamine during its electropolymerization. The mechanism’s complexity is also responsible for the electrochemical instabilities during electro-oxidation. In order to understand these instabilities it’s necessary to develop the mathematical model that is capable to describe the behavior of the system. It also helps us to esteem the influence of the electrochemical instabilities, by which it may be accompanied. The goal of this work is to describe an electrochemical oxidation and polymerization of dopamine that will provide an important connection between the electrochemical detection of biologically active compounds and their electropolymerization for electrode modification. Dopamine ; Electrochemistry ; Polymerization ; Monomer ; Polymer ; Electrode ; Materials science ; Chemistry ; Combinatorial chemistry ; Chemical engineering ; Nanotechnology ; Neuroscience ; Organic chemistry ; Physical chemistry ; Biology Conducting polymers and applications ; Electrochemical sensors and biosensors ; Electrochemical Analysis and Applications