jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Somboon Chaemchuen | Xuan Xiao | Nikom Klomkliang | Mekhman S. Yusubov | Francis Verpoort
Source: Preprints.org (preprint, 2018-07-13)
Field: Chemistry — Inorganic Chemistry

Tunable Metal-Organic Frameworks for Heat Transformation Applications Metal-Organic Frameworks (MOFs) are a subclass of porous materials that have unique properties such as varieties of structures from different metals and organic linkers, tunable porosity from a structure or framework design, etc. Moreover, modification/functionalization of the material structure could optimize the material properties and demonstrate high potential for a selected application. MOF materials exhibit exceptional properties and make these materials widely applicable including in energy storage and heat transformation applications. This review aims to give a broad overview of MOFs and their development as adsorbent materials having the potential for heat transformation applications. We summarize current investigations, developments, and possibilities of metal-organic frameworks (MOFs) especially the tuning of the porosity and hydrophobic/hydrophilic design required for this specific application. These materials applied as adsorbent are promising in the thermal driven adsorption for heat transformation using water as working fluid and related application. Porosity ; Metal-organic framework ; Materials science ; Adsorption ; Transformation (genetics) ; Surface modification ; Porous medium ; Nanotechnology ; Material Design ; Thermal ; Process engineering ; Chemical engineering ; Composite material ; Organic chemistry ; Chemistry ; Engineering ; Thermodynamics Metal-Organic Frameworks: Synthesis and Applications ; Enhanced Oil Recovery Techniques ; Phase Equilibria and Thermodynamics
Authors: Hajime Nakajima | Katja Loos | Shinobu Ishizu | Yoshiharu Kimura
Source: Macromolecular Rapid Communications (article, 2018-05-11)
Field: Materials Science — Biomaterials

Ring‐Opening Polymerization of a New Diester Cyclic Dimer of Mandelic and Glycolic Acid: An Efficient Synthesis Method for Derivatives of Amorphous Polyglycolide with High <i>T</i><sub>g</sub> In this study, poly(mandelate-co-glycolate) (PMG), a modified polyglycolide (PGL), is prepared by ring-opening polymerization (ROP) of L-3-phenyl-1,4-dioxane-2,5-dione (PDD); the cyclic dimer of biobased mandelic acid and glycolic acid. The resulting polymer shows an increased glass transition temperature (T<sub>g</sub> ) due to the incorporation of phenyl groups in the chain. High molecular weight PMG is obtained by bulk ROP at 150 °C, and it exhibits a glassy amorphous state with enhanced thermal properties such as a T<sub>g</sub> being 35 °C higher than conventional PGL. PDD is also copolymerized with glycolide (GL) and lactide (LA), resulting in poly(mandelate-co-glycolate/glycolate) ((P(MG/GL)) with GL and poly(mandelate-co-glycolate/lactide) ((P(MG/LA)) with LA. The thermal properties of P(MG/GL) and P(MG/LA) are found to be distinctly different from PMG and conventional PGL and polylactide, and they are tunable with a changing molar ratio of PDD, GL, and LA. Therefore, PDD opens an elegant way to control and tailor the properties of biobased polyesters. Glycolic acid ; Polymer chemistry ; Ring-opening polymerization ; Polyester ; Polymerization ; Materials science ; Mandelic acid ; Amorphous solid ; Glass transition ; Dimer ; Lactide ; Polymer ; Chemistry ; Lactic acid ; Organic chemistry ; Composite material biodegradable polymer synthesis and properties ; Carbon dioxide utilization in catalysis ; Polyoxometalates: Synthesis and Applications
Authors: Sahar Saremi | Ran Gao | Arvind Dasgupta | Lane W. Martin
Source: eScholarship (California Digital Library) (article, 2018-01-01)
Field: Materials Science — Ceramics and Composites

New facets for the role of defects in ceramics Ceramic ; Materials science ; Mineralogy ; Engineering physics ; Metallurgy ; Chemistry ; Engineering Advanced ceramic materials synthesis
Authors: Yong Yi | Xiaoyang Zheng | Zhibing Fu | Chaoyang Wang | Xibin Xu | Xiulan Tan
Source: Materials (article, 2018-03-05)
Field: Materials Science — Materials Chemistry

Multi-Scale Modeling for Predicting the Stiffness and Strength of Hollow-Structured Metal Foams with Structural Hierarchy This work was inspired by previous experiments which managed to establish an optimal template-dealloying route to prepare ultralow density metal foams. In this study, we propose a new analytical-numerical model of hollow-structured metal foams with structural hierarchy to predict its stiffness and strength. The two-level model comprises a main backbone and a secondary nanoporous structure. The main backbone is composed of hollow sphere-packing architecture, while the secondary one is constructed of a bicontinuous nanoporous network proposed to describe the nanoscale interactions in the shell. Firstly, two nanoporous models with different geometries are generated by Voronoi tessellation, then the scaling laws of the mechanical properties are determined as a function of relative density by finite volume simulation. Furthermore, the scaling laws are applied to identify the uniaxial compression behavior of metal foams. It is shown that the thickness and relative density highly influence the Young's modulus and yield strength, and vacancy defect determines the foams being self-supported. The present study provides not only new insights into the mechanical behaviors of both nanoporous metals and metal foams, but also a practical guide for their fabrication and application. Materials science ; Stiffness ; Hierarchy ; Scale (ratio) ; Composite material ; Structural engineering ; Engineering ; Physics Nanoporous metals and alloys ; Cellular and Composite Structures ; Pickering emulsions and particle stabilization
Authors: Rizwan Ali | Muhammad Rizwan Saleem | M. Roussey | Jari Turunen | Seppo Honkanen
Source: Scientific Reports (article, 2018-10-04)
Field: Materials Science — Surfaces, Coatings and Films

Fabrication of buried nanostructures by atomic layer deposition We present a method for fabricating buried nanostructures by growing a dielectric cover layer on a corrugated surface profile by atomic layer deposition of TiO<sub>2</sub>. Selecting appropriate process parameters, the conformal growth of TiO<sub>2</sub> results in a smooth, nearly flat-top surface of the structure. Such a hard surface can be easily cleaned without damage, making the nanostructure reusable after contamination. The technique has wide applicability in resonance-domain diffractive optics and in realization of quasi-planar metamaterials. We discuss design issues of such optical elements and demonstrate the method by fabricating narrow-band spectral filters based on the guided-mode resonance effect. These elements have strong potential for, e.g., sensing applications in harsh conditions. Nanostructure ; Atomic layer deposition ; Fabrication ; Planar ; Materials science ; Deposition (geology) ; Layer (electronics) ; Dielectric ; Metamaterial ; Optoelectronics ; Resonance (particle physics) ; Realization (probability) ; Nanotechnology ; Conformal map ; Computer science ; Physics Optical Coatings and Gratings ; Photonic and Optical Devices ; Photonic Crystals and Applications
Authors: Péter Bárány | Rita Szabó | Imre Kovács | Tamás Czuczi | Csenge Lilla Szabó | Angéla Takács | Eszter Lajkó | Orsolya Láng | László Kőhidai | Gitta Schlosser | Szilvia Bősze | Gábor Mező | Ferenc Hudecz | Antal Csámpai
Source: Molecules (article, 2018-09-03)
Field: Chemistry — Organic Chemistry

Ferrocene-Containing Impiridone (ONC201) Hybrids: Synthesis, DFT Modelling, In Vitro Evaluation, and Structure–Activity Relationships Inspired by the well-established clinical evidence about the interplay between apoptotic TRAIL (tumour necrosis factor-related apoptosis-inducing ligand) mechanism and reactive oxygen species (ROS)-mediated oxidative stress, a set of novel ONC201 hybrids containing the impiridone core and one or two differently positioned ferrocenylalkyl groups were synthesised in our present work. These two types of residues have been implicated in the aforementioned mechanisms associated with cytotoxic activity. A straightforward, primary amine-based synthetic approach was used allowing the introduction of a variety of <i>N</i>-substituents into the two opposite regions of the heterocyclic skeleton. Reference model compounds with benzyl and halogenated benzyl groups were also synthesised and tested. The in vitro assays of the novel impiridones on five malignant cell lines disclosed characteristic structure-activity relationship (SAR) featuring significant substituent-dependent activity and cell-selectivity. A possible contribution of ROS-mechanism to the cytotoxicity of the novel metallocenes was suggested by density functional theory (DFT)studies on simplified models. Accordingly, unlike the <i>mono</i>-ferrocenylalkyl-substituted products, the compounds containing two ferrocenylalkyl substituents in the opposite regions of the impiridone core display a much more pronounced long-term cytotoxic effect against A-2058 cell line than do the organic impiridones including ONC201 and ONC212. Furthermore, the prepared <i>bis</i>-metallocene derivatives also present substantial activity against COLO-205- and EBC-1 cell lines. Chemistry ; Substituent ; Stereochemistry ; Cytotoxicity ; Structure–activity relationship ; Reactive oxygen species ; Ferrocene ; Amine gas treating ; In vitro ; Apoptosis ; Cell culture ; Combinatorial chemistry ; Biochemistry ; Biology ; Organic chemistry Ferrocene Chemistry and Applications ; Metal complexes synthesis and properties ; Synthesis and Biological Evaluation
Authors: Tushagu Abudouwufu | Sambasivam Sangaraju | Ying Wan | Ayituerxun Abudoureyimu | Taximaiti Yusufu | Hairegu Tuxun | Aierken Sidike
Source: Journal of Electronic Materials (article, 2018-09-22)
Field: Materials Science — Materials Chemistry

Energy Transfer Behavior and Color-Tunable Properties of Ca2Al2SiO7:RE3+ (RE3+ = Tm3+, Dy3+, Tm3+/Dy3+) for White-Emitting Phosphors Tm3+/Dy3+-codoped Ca2Al2SiO7 phosphors have been synthesized using a high-temperature solid-state reaction method. The crystal structure, x-ray diffraction patterns, and photoluminescence (PL) properties of the rare-earth (RE) ions, and energy transfer (ET) processes between RE ions, were investigated in detail. The quenching concentration of Tm3+ and Dy3+ singly doped in Ca2Al2SiO7 was determined to be 0.006 mol and 0.02 mol, respectively. Under excitation at 357 nm, Ca2Al2SiO7:Tm3+ phosphors showed emission lines of Tm3+ corresponding to 1D2 → 3F4 and 1G4 → 3H6 transitions. Efficient ET from Tm3+ to Dy3+ ions was observed, leading to color-tunable emissions of Ca2Al2SiO7:0.006Tm3+,xDy3+ (x = 0 mol to 0.02 mol) phosphors. Theoretical calculations revealed that the efficiency of the ET gradually increased with increase in the Dy3+ ion concentration, reaching a maximum of ∼ 42.1% at Tm3+ ion concentration of 0.006 mol. Furthermore, at 473 K, the quantum efficiency was calculated to be 79.8% at room temperature, confirming the good thermal stability of the Ca2Al2SiO7:0.006Tm3+,xDy3+ phosphors. Phosphor ; Energy transfer ; Materials science ; Chemistry ; Optoelectronics Luminescence Properties of Advanced Materials ; Microwave Dielectric Ceramics Synthesis ; Ammonia Synthesis and Nitrogen Reduction
Authors: Anupama Achal Sharan | Ashwini N. Nikam | Abdul Jaleel | Vaijayanti A. Tamhane | Srinivasa P. Rao
Source: Tropical Plant Biology (article, 2018-04-13)
Field: Chemistry — Spectroscopy

Method for Label-Free Quantitative Proteomics for Sorghum bicolor L. Moench Sorghum (Sorghum bicolor L. Moench) is a rapidly emerging high biomass feedstock for bioethanol and lignocellulosic biomass production. The robust varietal germplasm of sorghum and its completed genome sequence provide the necessary genetic and molecular tools to study and engineer the biotic/abiotic stress tolerance. Traditional proteomics approaches for outlining the sorghum proteome have many limitations like, demand for high protein amounts, reproducibility and identification of only few differential proteins. In this study, we report a gel-free, quantitative proteomic method for in-depth coverage of the sorghum proteome. This novel method combining phenol extraction and methanol chloroform precipitation gives high total protein yields for both mature sorghum root and leaf tissues. We demonstrate successful application of this method in comparing proteomes of contrasting cultivars of sorghum, at two different phenological stages. Protein identification and relative quantification analyses were performed by a label-free liquid chromatography tandem mass spectrometry (LC/MS-MS) analyses. Several unique proteins were identified respectively from sorghum tissues, specifically 271 from leaf and 774 from root tissues, with 193 proteins common in both tissues. Using gene ontology analysis, the differential proteins identified were finely corroborated with their leaf/root tissue specific functions. This method of protein extraction and analysis would contribute substantially to generate in-depth differential protein data in sorghum as well as related species. It would also increase the repertoire of methods uniquely suited for gel-free plant proteomics that are increasingly being developed for studying abiotic and biotic stress responses. Sorghum ; Proteomics ; Proteome ; Biology ; Abiotic stress ; Abiotic component ; Biotic stress ; Botany ; Agronomy ; Gene ; Biochemistry Advanced Proteomics Techniques and Applications ; GABA and Rice Research ; Metabolomics and Mass Spectrometry Studies
Authors: Experimental Design Bureau " | Evgeniy V. KOSMODEMYANSKY | Fakel" | A. T. Nagiev | JSC «SRC «Progress» | D. Izratov | V. Kirpichev | Павел Николаевич Давыдов | TSNIIMASH | A. Markarova | I. Kozlova | A. Okutin | A. Pustovalov
Source: Ontology of Designing (article, 2018-01-01)
Field: Materials Science — General Materials Science

SPACE ROCKET COMPLEX PROJECT ON THE BASIS OF A SUPER-LIGHT CLASS ROCKET-CARRIER The article reviews the need of the rocket and space industry for rocket carrier (RC) intended for launching small spacecraft (SSC), namely in the RC of the superlight class (RC SLC). The most famous foreign projects of ultralight class launch vehicles, their features and characteristics are described. They were compared with the proposed RC SLC "Akvilon" on the main technical and economic indicators. The possibility of testing and applying the new technological and structural solutions on the proposed RC SLC "Akvilon" is considered: application in the design of polymer composites (carbon fiber-reinforced plastics in the design of both dry compartments and with the use of special wall coating, fuel tanks; carbon-graphite plastics in the design of high-heat loaded elements: combustion chambers, cusps of the head fairing, fairing of the 1st accelerator and front edges of the wing consoles (in the reusable configuration)); the use of additive technologies in the manufacture of the propulsion system, power elements using topological optimization at the stage of their design; new components of fuel, which allow to reduce the cost of fuel and the maintenance of the remote control of the launch vehicle during post-flight diagnostics, as well as to improve the energy characteristics of the launch vehicle and significantly simplify the layout of the compartments of the launch vehicle and the cooling system for the walls of the combustion chamber; creation of the returned and reused as a result of operational semi-automatic post-flight diagnostics of the 1st rocket unit. A new approach to research in this direction is the use of an integrated approach to examining current trends in the field of rocket production and taking into account the current state of the launch services market. Rocket (weapon) ; Aerospace engineering ; Spacecraft ; Propulsion ; Spacecraft propulsion ; Mechanical engineering ; Engineering ; Automotive engineering Material Properties and Applications ; Rocket and propulsion systems research
Authors: Patrícia Gotardo Machado | Alessandro Cazonatto Galvão | Weber da Silva Robazza | Pedro F. Arce | Bruna E. Hochscheidt
Source: Industrial & Engineering Chemistry Research (article, 2018-07-09)
Field: Materials Science — Materials Chemistry

Phase Equilibrium Involving Xylitol, Water, and Ethylene Glycol or 1,2-Propylene Glycol: Experimental Data, Activity Coefficient Modeling, and Prediction with Artificial Neural Network-Molecular Descriptors The xylitol molecule is an important building block that can be used in the production of such interesting chemicals as ethylene glycol and 1,2-propylene glycol. The development of productive processes that enable this transformation depends on various experimental and theoretical information. In order to supply part of this demand, this work sought to study the solubility of xylitol in binary liquid solutions formed by water, ethylene glycol, and 1,2-propylene glycol in the temperature range between 293.15 and 323.15 K, covering the entire molar composition range of the solution. The Jouyban–Acree, NRTL, and UNIQUAC models were used in the correlation of experimental data, and the mUNIFAC model was applied in the prediction of experimental data. In addition, an artificial neural network associated with molecular descriptors was developed to simulate the data. Xylitol showed solubility in the pure components with decreasing values in the following order: water, ethylene glycol, and 1,2-propylene glycol. The solubility in binary solutions had intermediate values according to the intermediate concentration values. The models used proved capable of correlating or predicting the experimental data. The artificial neural networks had a satisfactory performance in the data simulation, and the best observed architecture used four layers of the type 7-3-3-1. Ethylene glycol ; Xylitol ; UNIQUAC ; Polyvinyl alcohol ; Solubility ; Non-random two-liquid model ; Thermodynamics ; Materials science ; Chemistry ; Artificial neural network ; Polyol ; Chemical engineering ; Organic chemistry ; Aqueous solution ; Activity coefficient ; Computer science Crystallization and Solubility Studies ; Process Optimization and Integration ; Analytical Chemistry and Chromatography
Authors: Masato Sumita | Xiufeng Yang | Shinsuke Ishihara | Ryo Tamura | Koji Tsuda
Source: ChemRxiv (preprint, 2018-01-01)
Field: Materials Science — Materials Chemistry

Hunting for Organic Molecules with Artificial Intelligence: Molecules Optimized for Desired Excitation Energies &lt;p&gt;&lt;a&gt;&lt;/a&gt;This work presents a proof-of-concept study in artificial-intelligence-assisted (AI-assisted) chemistry where a machine-learning-based molecule generator is coupled with density functional theory (DFT) calculations, synthesis, and measurement. Although deep-learning-based molecule generators have shown promise, it is unclear to what extent they can be useful in real-world materials development. To assess the reliability of AI-assisted chemistry, we prepared a platform using the ChemTS molecule generator and a DFT simulator, and attempted to generate novel photo-functional molecules whose lowest excited states lie at desired energetic levels. A ten-day run on 12 cores discovered 86potential photo-functional molecules around target lowest excitation levels, designated as 200, 300, 400, 500, and 600 nm. Among the molecules discovered, six were synthesized and five were confirmed to reproduce DFT predictions in ultraviolet visible absorption measurements. This result shows the potential of AI-assisted chemistry to discover ready-to-synthesize novel molecules with modest computational resources.&lt;br&gt;&lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;/p&gt;&lt;div&gt;The Android robot is reproduced or modified from work created and shared by Google and used &lt;/div&gt;&lt;div&gt;according to terms described in the Creative Commons 3.0 Attribution License.&lt;/div&gt; Density functional theory ; Molecule ; Excited state ; Time-dependent density functional theory ; Chemistry ; Artificial intelligence ; Computer science ; Nanotechnology ; Computational chemistry ; Physics ; Materials science ; Atomic physics Machine Learning in Materials Science ; Chemistry and Chemical Engineering ; Various Chemistry Research Topics
Authors: Kien Do | Truyen Tran | Svetha Venkatesh
Source: arXiv (Cornell University) (preprint, 2018-12-22)
Field: Materials Science — Materials Chemistry

Graph Transformation Policy Network for Chemical Reaction Prediction We address a fundamental problem in chemistry known as chemical reaction product prediction. Our main insight is that the input reactant and reagent molecules can be jointly represented as a graph, and the process of generating product molecules from reactant molecules can be formulated as a sequence of graph transformations. To this end, we propose Graph Transformation Policy Network (GTPN) -- a novel generic method that combines the strengths of graph neural networks and reinforcement learning to learn the reactions directly from data with minimal chemical knowledge. Compared to previous methods, GTPN has some appealing properties such as: end-to-end learning, and making no assumption about the length or the order of graph transformations. In order to guide model search through the complex discrete space of sets of bond changes effectively, we extend the standard policy gradient loss by adding useful constraints. Evaluation results show that GTPN improves the top-1 accuracy over the current state-of-the-art method by about 3% on the large USPTO dataset. Our model's performances and prediction errors are also analyzed carefully in the paper. Computer science ; Graph ; Artificial neural network ; Chemical space ; Reinforcement learning ; Theoretical computer science ; Transformation (genetics) ; Algorithm ; Artificial intelligence ; Chemistry Machine Learning in Materials Science ; Advanced Graph Neural Networks ; Topic Modeling
Authors: D. Wilk-Kołodziejczyk | Krzysztof Regulski | T. Giętka | G. Gumienny | Krzysztof Jaśkowiec | S. Kluska-Nawarecka
Source: Journal of Materials Engineering and Performance (article, 2018-10-26)
Field: Materials Science — Materials Chemistry

The Selection of Heat Treatment Parameters to Obtain Austempered Ductile Iron with the Required Impact Strength The effect of austempering parameters on impact energy of non-alloyed cast iron with nodular graphite was examined. The analysis involved the austenitizing temperature in the range of 830-950 °C for the time of 60 min and the austempering temperature in the range of 300-400 °C for the time of 8, 16, 32 and 64 min. The value of the impact energy KV was determined. It has been found that the austenitizing temperature and austempering conditions affect the impact energy of ADI. The conducted analytical studies helped to develop a method for the selection of heat treatment parameters to obtain the ausferritic ductile iron with appropriate impact energy KV. The applied machine learning methods included support vector machine, decision trees, artificial neural networks and the method of variational component analysis. Austempering ; Materials science ; Austenite ; Cast iron ; Ductile iron ; Metallurgy ; Graphite ; Range (aeronautics) ; Atmospheric temperature range ; Artificial neural network ; Composite material ; Thermodynamics ; Bainite ; Microstructure ; Machine learning ; Computer science Material Properties and Failure Mechanisms ; Coal Combustion and Slurry Processing ; Metallurgical Processes and Thermodynamics