jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Núria Carranco | Mireia Farrés-Cebrián | Javier Saurina | Óscar Núñez
Source: Foods (article, 2018-03-21)
Field: Chemistry — Organic Chemistry

Authentication and Quantitation of Fraud in Extra Virgin Olive Oils Based on HPLC-UV Fingerprinting and Multivariate Calibration High performance liquid chromatography method with ultra-violet detection (HPLC-UV) fingerprinting was applied for the analysis and characterization of olive oils, and was performed using a Zorbax Eclipse XDB-C8 reversed-phase column under gradient elution, employing 0.1% formic acid aqueous solution and methanol as mobile phase. More than 130 edible oils, including monovarietal extra-virgin olive oils (EVOOs) and other vegetable oils, were analyzed. Principal component analysis results showed a noticeable discrimination between olive oils and other vegetable oils using raw HPLC-UV chromatographic profiles as data descriptors. However, selected HPLC-UV chromatographic time-window segments were necessary to achieve discrimination among monovarietal EVOOs. Partial least square (PLS) regression was employed to tackle olive oil authentication of Arbequina EVOO adulterated with Picual EVOO, a refined olive oil, and sunflower oil. Highly satisfactory results were obtained after PLS analysis, with overall errors in the quantitation of adulteration in the Arbequina EVOO (minimum 2.5% adulterant) below 2.9%. Chromatography ; High-performance liquid chromatography ; Adulterant ; Chemistry ; Gradient elution ; Olive oil ; Vegetable oil ; Formic acid ; Chemometrics ; Sunflower oil ; Food science Edible Oils Quality and Analysis ; Identification and Quantification in Food ; Spectroscopy and Chemometric Analyses
Authors: Samraj Mollick | Soumya Mukherjee | Dongwook Kim | Zhiwei Qiao | Aamod V. Desai | Rajat Saha | Yogeshwar D. More | Jianwen Jiang | Myoung Soo Lah | Sujit K. Ghosh
Source: Angewandte Chemie International Edition (article, 2018-12-04)
Field: Chemistry — Inorganic Chemistry

Hydrophobic Shielding of Outer Surface: Enhancing the Chemical Stability of Metal–Organic Polyhedra Metal-organic polyhedra (MOP) are a promising class of crystalline porous materials with multifarious potential applications. Although MOPs and metal-organic frameworks (MOFs) have similar potential in terms of their intrinsic porosities and physicochemical properties, the exploitation of carboxylate MOPs is still rudimentary because of the lack of systematic development addressing their chemical stability. Herein we describe the fabrication of chemically robust carboxylate MOPs via outer-surface functionalization as an a priori methodology, to stabilize those MOPs system where metal-ligand bond is not so strong. Fine-tuning of hydrophobic shielding is key to attaining chemical inertness with retention of the framework integrity over a wide range of pH values, in strong acidic conditions, and in oxidizing and reducing media. These results are further corroborated by molecular modelling studies. Owing to the unprecedented transition from instability to a chemically ultra-stable regime using a rapid ambient-temperature gram-scale synthesis (within seconds), a prototype strategy towards chemically stable MOPs is reported. Oxidizing agent ; Surface modification ; Chemical stability ; Carboxylate ; Chemistry ; Metal-organic framework ; Electromagnetic shielding ; Ligand (biochemistry) ; Metal ; Chemical engineering ; Nanotechnology ; Fabrication ; Polyhedron ; Porosity ; Materials science ; Adsorption ; Organic chemistry ; Physical chemistry ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Nanoplatforms for cancer theranostics ; Covalent Organic Framework Applications
Authors: Vijaykumar S. Marakatti | Sebastian C. Peter
Source: Progress in Solid State Chemistry (article, 2018-09-11)
Field: Materials Science — Materials Chemistry

Synthetically tuned electronic and geometrical properties of intermetallic compounds as effective heterogeneous catalysts Intermetallic ; Bimetallic strip ; Catalysis ; Steric effects ; Electronic effect ; Characterization (materials science) ; Palladium ; Materials science ; Platinum ; Electronic structure ; Nickel ; Metal ; Nanotechnology ; Chemistry ; Computational chemistry ; Metallurgy ; Organic chemistry ; Alloy Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Nanomaterials for catalytic reactions
Authors: Daniel Franz | Shigeyoshi Inoue
Source: Chemistry - A European Journal (review, 2018-08-16)
Field: Chemistry — Organic Chemistry

Cationic Complexes of Boron and Aluminum: An Early 21st Century Viewpoint Boron and aluminum are lighter Group 13 elements, found in daily life commodities, and considered environmentally benign. Nevertheless, they markedly differ in their elemental properties (e.g., metal character, atomic radius). The use of Lewis acidic complexes of boron and aluminum for methods of bond activation and catalysis (e.g., hydrogenation of unsaturated substrates, polymerization of olefins and epoxides) is quickly expanding. The introduction of cationic charge may boost the metalloid-centered Lewis acidity and allow for its fine-tuning particularly with regard to preference for "hard" or "soft" Lewis bases (i.e., substrates). Especially the isolation of low-coordinate cations (number of ligand atoms smaller than four) demands elaborate techniques of thermodynamic and kinetic stabilization (i.e., electronic saturation and steric shielding) by a ligand system. Furthermore, the properties of the solvent and the counteranion must be considered with care. Here, selected examples of boron and aluminum cations are described. Cationic polymerization ; Lewis acids and bases ; Boron ; Steric effects ; Chemistry ; Ligand (biochemistry) ; Aluminium ; Main group element ; Trihalide ; Metal ; Catalysis ; Inorganic chemistry ; Polymerization ; Solvent ; Polymer chemistry ; Organic chemistry ; Transition metal ; Polymer Organoboron and organosilicon chemistry ; Synthesis and characterization of novel inorganic/organometallic compounds ; Organometallic Complex Synthesis and Catalysis
Authors: Sajjad Mohammadi | Seeram Ramakrishna | Sophie Laurent | Mohammad Ali Shokrgozar | Dariush Semnani | Davoud Sadeghi | Shahin Bonakdar | Mohsen Akbari
Source: Journal of Biomedical Materials Research Part A (article, 2018-11-28)
Field: Materials Science — Biomaterials

Fabrication of Nanofibrous PVA/Alginate‐Sulfate Substrates for Growth Factor Delivery Providing affinity sites on alginate (ALG) matrix enables specific binding of growth factors to the polymer backbone and allows their release in a controlled fashion. In this study, we used a blend of alginate sulfate (ALG-S) and polyvinyl alcohol (PVA) to fabricate electrospun scaffolds capable of delivering a heparin-like growth factor, transforming growth factor-beta1 (TGF-β1). The alginate was sulfated with different degrees of sulfation (DS, from 0.8, 3.4 to 12.4%) by a simple process. The success of sulfation was determined by Fourier-transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (NMR), elemental analysis, ultraviolet (UV) spectroscopy and staining with dimethylmethylene blue. The physical-mechanical properties of nanofibrous mats were characterized by scanning electron microscopy (SEM), FTIR, energy-dispersive X-ray spectroscopy (EDX), tensile strength and mass loss analysis. Additionally, the release kinetics of transforming growth factor-β1 (TGF-β1) from PVA/ALG-S and PVA/ALG scaffolds were compared. The results showed that the binding and entrapment of TGF-β1 to the nanofibrous scaffolds are improved by the addition of sulfate group to alginate. In conclusion, our results support that nanofibrous scaffold based on PVA/ALG-S can deliver growth factors in tissue engineering application. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 107A: 403-413, 2019. Materials science ; Polyvinyl alcohol ; Sulfation ; Fourier transform infrared spectroscopy ; Chemical engineering ; Polymer ; Scanning electron microscope ; Electrospinning ; Tissue engineering ; Polymer chemistry ; Nuclear chemistry ; Composite material ; Biomedical engineering ; Chemistry ; Biochemistry Electrospun Nanofibers in Biomedical Applications ; 3D Printing in Biomedical Research ; Hydrogels: synthesis, properties, applications
Authors: Philipp C. Verpoort | Paul M. Macdonald | G. J. Conduit
Source: Computational Materials Science (article, 2018-02-13)
Field: Materials Science — Materials Chemistry

Materials data validation and imputation with an artificial neural network Artificial neural network ; Computer science ; Exploit ; Property (philosophy) ; Imputation (statistics) ; Data mining ; Artificial intelligence ; Missing data ; Data quality ; Machine learning ; Engineering Machine Learning in Materials Science ; Hydrogen embrittlement and corrosion behaviors in metals ; X-ray Diffraction in Crystallography
Authors: Truong Son Hy | Shubhendu Trivedi | Horace Pan | Brandon Anderson | Risi Kondor
Source: The Journal of Chemical Physics (article, 2018-06-27)
Field: Materials Science — Materials Chemistry

Predicting molecular properties with covariant compositional networks Density functional theory (DFT) is the most successful and widely used approach for computing the electronic structure of matter. However, for tasks involving large sets of candidate molecules, running DFT separately for every possible compound of interest is forbiddingly expensive. In this paper, we propose a neural network based machine learning algorithm which, assuming a sufficiently large training sample of actual DFT results, can instead learn to predict certain properties of molecules purely from their molecular graphs. Our algorithm is based on the recently proposed covariant compositional networks framework and involves tensor reduction operations that are covariant with respect to permutations of the atoms. This new approach avoids some of the representational limitations of other neural networks that are popular in learning from molecular graphs and yields promising results in numerical experiments on the Harvard Clean Energy Project and QM9 molecular datasets. Covariant transformation ; Density functional theory ; Computer science ; Tensor (intrinsic definition) ; Artificial neural network ; Theoretical computer science ; Artificial intelligence ; Reduction (mathematics) ; Algorithm ; Computational chemistry ; Mathematics ; Chemistry ; Pure mathematics ; Geometry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Various Chemistry Research Topics
Authors: Karteek K. Bejagam | Samrendra Singh | Yaxin An | Sanket A. Deshmukh
Source: The Journal of Physical Chemistry Letters (article, 2018-07-19)
Field: Materials Science — Materials Chemistry

Machine-Learned Coarse-Grained Models Optimizing force-field (FF) parameters to perform molecular dynamics (MD) simulations is a challenging and time-consuming process. We present a novel FF optimization framework that integrates MD simulations with particle swarm optimization (PSO) algorithm and artificial neural network (ANN). This new ANN-assisted PSO framework was used to develop transferable coarse-grained (CG) models for D<sub>2</sub>O and DMF as a proof of concept. The PSO algorithm was used to generate the set of input FF parameters for the MD simulations of the CG models of these solvents, which were optimized to reproduce their experimental properties. Herein, for the first time, a reverse approach was employed for on-the-fly training of the ANN model, where results (solvent properties) obtained from the MD simulations and their corresponding FF parameters were used as inputs and outputs, respectively. The ANN model was then required to predict a set of new FF parameters, which were tested for their ability to predict the desired experimental properties. This new framework can be extended to integrate any optimization algorithm with ANN and MD simulations to accelerate the FF development. Particle swarm optimization ; Computer science ; Artificial neural network ; Set (abstract data type) ; Process (computing) ; Force field (fiction) ; Molecular dynamics ; Field (mathematics) ; Algorithm ; Optimization algorithm ; Biological system ; Mathematical optimization ; Artificial intelligence ; Mathematics ; Chemistry ; Computational chemistry Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Protein Structure and Dynamics
Authors: Mateusz Ciszewski | A. Koszorek | Tomasz Radko | Piotr Szatkowski | Dawid Janas
Source: Journal of Electronic Materials (article, 2018-11-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Review of the Selected Carbon-Based Materials for Symmetric Supercapacitor Application Carbon materials are among the most commonly used components of supercapacitor electrodes. Particularly, active carbons are recognized as cheap, available, and easily tailored materials. However, the carbon family, i.e. carbon products and carbon precursors, consists of many members. In this manuscript some of these materials, including laboratory scale-produced carbon gels, carbon nanotubes and carbonized materials, as well as industrial scale-produced graphites, pitches, coke and coal, were compared. Discussion was preceded by a short history of supercapacitors and review of each type of tested material, from early beginning to state-of-the-art. Morphology and structure of the materials were analyzed (specific surface area, pore volume and interlayer spacing determination), to evaluate their applicability in energy storage. Thermal analysis was used to determine the stability and purity. Finally, electrochemical evaluation using cyclic voltammetry, galvanostatic charge–discharge and electrochemical impedance spectroscopy was performed. Outcomes of each analytical technique were summarized in different sections. Supercapacitor ; Materials science ; Carbon fibers ; Carbonization ; Carbon nanotube ; Dielectric spectroscopy ; Cyclic voltammetry ; Carbide-derived carbon ; Nanotechnology ; Coke ; Chemical engineering ; Electrochemistry ; Composite material ; Electrode ; Chemistry ; Carbon nanofiber ; Metallurgy ; Scanning electron microscope Supercapacitor Materials and Fabrication ; Advancements in Battery Materials ; Graphene research and applications
Authors: Friederike Langhauser | Ana I. Casas | Vu-Thao-Vi Dao | Emre Güney | Jörg Menche | Eva Geuß | Pamela W. M. Kleikers | Manuela G. López | Albert-Ĺaszló Barabási | Christoph Kleinschnitz | Harald Schmidt
Source: npj Systems Biology and Applications (article, 2018-01-31)
Field: Chemistry — Organic Chemistry

A diseasome cluster-based drug repurposing of soluble guanylate cyclase activators from smooth muscle relaxation to direct neuroprotection Network medicine utilizes common genetic origins, markers and co-morbidities to uncover mechanistic links between diseases. These links can be summarized in the diseasome, a comprehensive network of disease-disease relationships and clusters. The diseasome has been influential during the past decade, although most of its links are not followed up experimentally. Here, we investigate a high prevalence unmet medical need cluster of disease phenotypes linked to cyclic GMP. Hitherto, the central cGMP-forming enzyme, soluble guanylate cyclase (sGC), has been targeted pharmacologically exclusively for smooth muscle modulation in cardiology and pulmonology. Here, we examine the disease associations of sGC in a non-hypothesis based manner in order to identify possibly previously unrecognized clinical indications. Surprisingly, we find that sGC, is closest linked to neurological disorders, an application that has so far not been explored clinically. Indeed, when investigating the neurological indication of this cluster with the highest unmet medical need, ischemic stroke, pre-clinically we find that sGC activity is virtually absent post-stroke. Conversely, a heme-free form of sGC, apo-sGC, was now the predominant isoform suggesting it may be a mechanism-based target in stroke. Indeed, this repurposing hypothesis could be validated experimentally in vivo as specific activators of apo-sGC were directly neuroprotective, reduced infarct size and increased survival. Thus, common mechanism clusters of the diseasome allow direct drug repurposing across previously unrelated disease phenotypes redefining them in a mechanism-based manner. Specifically, our example of repurposing apo-sGC activators for ischemic stroke should be urgently validated clinically as a possible first-in-class neuroprotective therapy. Drug repositioning ; Neuroprotection ; Repurposing ; Medicine ; Stroke (engine) ; Mechanism (biology) ; Disease ; Neurology ; Pharmacology ; Drug ; Bioinformatics ; In vivo ; Phenotype ; Neuroscience ; Internal medicine ; Biology ; Gene ; Genetics Synthesis and Catalytic Reactions ; Phosphodiesterase function and regulation ; Neuroinflammation and Neurodegeneration Mechanisms
Authors: Sreekar B. Marpu | Erin N. Benton
Source: International Journal of Molecular Sciences (review, 2018-06-17)
Field: Materials Science — Biomaterials

Shining Light on Chitosan: A Review on the Usage of Chitosan for Photonics and Nanomaterials Research Chitosan (CS) is a natural polymer derived from chitin that has found its usage both in research and commercial applications due to its unique solubility and chemical and biological attributes. The biocompatibility and biodegradability of CS have helped researchers identify its utility in the delivery of therapeutic agents, tissue engineering, wound healing, and more. Industrial applications include cosmetic and personal care products, wastewater treatment, and corrosion protection, to name a few. Many researchers have published numerous reviews outlining the physical and chemical properties of CS, as well as its use for many of the above-mentioned applications. Recently, the cationic polyelectrolyte nature of CS was found to be advantageous for stabilizing fascinating photonic materials including plasmonic nanoparticles (e.g., gold and silver), semiconductor nanoparticles (e.g., zinc oxide, cadmium sulfide), fluorescent organic dyes (e.g., fluorescein isothiocyanate (FITC)), luminescent transitional and lanthanide complexes (e.g., Au(I) and Ru(II), and Eu(III)). These photonic systems have been extensively investigated for their usage in antimicrobial, wound healing, diagnostics, sensing, and imaging applications. Highlighted in this review are the different works involving some of the above-mentioned molecular-nano systems that are prepared or stabilized using the CS polymer. The advantages and the role of the CS for synthesizing and stabilizing the above-mentioned optically active materials have been illustrated. Chitosan ; Nanotechnology ; Biocompatibility ; Materials science ; Nanocomposite ; Polymer ; Nanomaterials ; Chemistry ; Organic chemistry Nanocomposite Films for Food Packaging ; Nanoparticles: synthesis and applications ; Quantum Dots Synthesis And Properties
Authors: Zhaoliang Liao | Nicolas Gauquelin | Robert J. Green | Knut Müller‐Caspary | Iván Lobato | Lin Li | Sandra Van Aert | Johan Verbeeck | Mark Huijben | Mathieu N. Grisolia | V. Rouco | Ralph El Hage | Javier E. Villegas | Alain Mercy | Manuel Bibès | Philippe Ghosez | G. A. Sawatzky | Guus Rijnders | Gertjan Koster
Source: Proceedings of the National Academy of Sciences (article, 2018-09-05)
Field: Materials Science — Materials Chemistry

Metal–insulator-transition engineering by modulation tilt-control in perovskite nickelates for room temperature optical switching In transition metal perovskites ABO<sub>3</sub>, the physical properties are largely driven by the rotations of the BO<sub>6</sub> octahedra, which can be tuned in thin films through strain and dimensionality control. However, both approaches have fundamental and practical limitations due to discrete and indirect variations in bond angles, bond lengths, and film symmetry by using commercially available substrates. Here, we introduce modulation tilt control as an approach to tune the ground state of perovskite oxide thin films by acting explicitly on the oxygen octahedra rotation modes-that is, directly on the bond angles. By intercalating the prototype SmNiO<sub>3</sub> target material with a tilt-control layer, we cause the system to change the natural amplitude of a given rotation mode without affecting the interactions. In contrast to strain and dimensionality engineering, our method enables a continuous fine-tuning of the materials' properties. This is achieved through two independent adjustable parameters: the nature of the tilt-control material (through its symmetry, elastic constants, and oxygen rotation angles), and the relative thicknesses of the target and tilt-control materials. As a result, a magnetic and electronic phase diagram can be obtained, normally only accessible by A-site element substitution, within the single SmNiO<sub>3</sub> compound. With this unique approach, we successfully adjusted the metal-insulator transition (MIT) to room temperature to fulfill the desired conditions for optical switching applications. Materials science ; Perovskite (structure) ; Tilt (camera) ; Rotation (mathematics) ; Condensed matter physics ; Superlattice ; Curse of dimensionality ; Optics ; Optoelectronics ; Crystallography ; Physics ; Chemistry ; Computer science ; Geometry Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Electronic and Structural Properties of Oxides
Authors: Dereje Kebebe | Yuanyuan Liu | Yumei Wu | Maikhone Vilakhamxay | Zhidong Liu | Jiawei Li
Source: International Journal of Nanomedicine (review, 2018-03-01)
Field: Materials Science — Biomaterials

Tumor-targeting delivery of herb-based drugs with cell-penetrating/tumor-targeting peptide-modified nanocarriers Cancer has become one of the leading causes of mortality globally. The major challenges of conventional cancer therapy are the failure of most chemotherapeutic agents to accumulate selectively in tumor cells and their severe systemic side effects. In the past three decades, a number of drug delivery approaches have been discovered to overwhelm the obstacles. Among these, nanocarriers have gained much attention for their excellent and efficient drug delivery systems to improve specific tissue/organ/cell targeting. In order to enhance targeting efficiency further and reduce limitations of nanocarriers, nanoparticle surfaces are functionalized with different ligands. Several kinds of ligand-modified nanomedicines have been reported. Cell-penetrating peptides (CPPs) are promising ligands, attracting the attention of researchers due to their efficiency to transport bioactive molecules intracellularly. However, their lack of specificity and in vivo degradation led to the development of newer types of CPP. Currently, activable CPP and tumor-targeting peptide (TTP)-modified nanocarriers have shown dramatically superior cellular specific uptake, cytotoxicity, and tumor growth inhibition. In this review, we discuss recent advances in tumor-targeting strategies using CPPs and their limitations in tumor delivery systems. Special emphasis is given to activable CPPs and TTPs. Finally, we address the application of CPPs and/or TTPs in the delivery of plant-derived chemotherapeutic agents. Nanocarriers ; Cell-penetrating peptide ; Peptide ; Drug delivery ; Pharmacology ; Medicine ; Cancer research ; Targeted drug delivery ; Nanotechnology ; Drug ; Materials science ; Chemistry ; Biochemistry Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery ; Curcumin's Biomedical Applications