jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Valeria Bugatti | Luigi Vertuccio | Gianluca Viscusi | Giuliana Gorrasi
Source: Nanomaterials (article, 2018-03-01)
Field: Materials Science — Materials Chemistry

Antimicrobial Membranes of Bio-Based PA 11 and HNTs Filled with Lysozyme Obtained by an Electrospinning Process Bio-based membranes were obtained using Polyamide 11 (PA11) from renewable sources and a nano-hybrid composed of halloysite nanotubes (HNTs) filled with lysozyme (50 wt % of lysozyme), as a natural antimicrobial molecule. Composites were prepared using an electrospinning process, varying the nano-hybrid loading (i.e., 1.0, 2.5, 5.0 wt %). The morphology of the membranes was investigated through SEM analysis and there was found to be a narrow average fiber diameter (0.3-0.5 μm). The mechanical properties were analyzed and correlated to the nano-hybrid content. Controlled release of lysozyme was followed using UV spectrophotometry and the release kinetics were found to be dependent on HNTs-lysozyme loading. The experimental results were analyzed by a modified Gallagher-Corrigan model. The application of the produced membranes, as bio-based pads, for extending the shelf life of chicken slices has been tested and evaluated. Electrospinning ; Lysozyme ; Antimicrobial ; Membrane ; Materials science ; Process (computing) ; Chemical engineering ; Nanotechnology ; Chemistry ; Composite material ; Computer science ; Engineering ; Organic chemistry ; Polymer ; Biochemistry Layered Double Hydroxides Synthesis and Applications ; Clay minerals and soil interactions ; Advanced Photocatalysis Techniques
Authors: М. Ф. Бутман | N. L. Ovchinnikov | N. S. Karasev | Н. Е. Кочкина | А. В. Агафонов | Alexandr V. Vinogradov
Source: Beilstein Journal of Nanotechnology (article, 2018-01-31)
Field: Chemistry — Inorganic Chemistry

Photocatalytic and adsorption properties of TiO<sub>2</sub>-pillared montmorillonite obtained by hydrothermally activated intercalation of titanium polyhydroxo complexes We report on a new approach for the synthesis of TiO<sub>2</sub>-pillared montmorillonite, where the pillars exhibit a high degree of crystallinity (nanocrystals) representing a mixture of anatase and rutile phases. The structures exhibit improved adsorption and photocatalytic activity as a result of hydrothermally activated intercalation of titanium polyhydroxo complexes (i.e., TiCl<sub>4</sub> hydrolysis products) in a solution with a concentration close to the sol formation limit. The materials, produced at various annealing temperatures from the intercalated samples, were characterized by infrared spectroscopy, differential scanning calorimetry (DSC)/thermogravimetric analysis (TGA), X-ray diffraction, dynamic light scattering (DLS) measurements, and liquefied nitrogen adsorption/desorption. The photocatalytic activity of the TiO<sub>2</sub>-pillared materials was studied using the degradation of anionic (methyl orange, MO) and cationic (rhodamine B, RhB) dyes in water under UV irradiation. The combined effect of adsorption and photocatalysis resulted in removal of 100% MO and 97.5% RhB (with an initial concentration of 40 mg/L and a photocatalyst-sorbent concentration of 1 g/L) in about 100 minutes. The produced TiO<sub>2</sub>-pillared montmorillonite showed increased photocatalytic activity as compared to the commercially available photocatalyst Degussa P25. Montmorillonite ; Intercalation (chemistry) ; Photocatalysis ; Adsorption ; Titanium ; Materials science ; Chemical engineering ; Inorganic chemistry ; Chemistry ; Catalysis ; Physical chemistry ; Composite material ; Metallurgy ; Organic chemistry Zeolite Catalysis and Synthesis ; TiO2 Photocatalysis and Solar Cells ; Advanced Photocatalysis Techniques
Authors: Beata Szefler
Source: International Journal of Nanomedicine (review, 2018-10-01)
Field: Chemistry — Organic Chemistry

Nanotechnology, from quantum mechanical calculations up to drug delivery There are several reasons why nanotechnology is currently considered as the leader among the most intensively developing research trends. Nanomatter often exhibits new properties, other than those of the morphology of a continuous solid. Also, new phenomena appear at the nanoscale, which are unknown in the case of microcrystalline objects. For this reason, nanomaterials have already found numerous applications that are described in this review. However, among intensively developed various branches of nanotechnology, nanomedicine and pharmacology stand out particularly, which opens new possibilities for the development of these disciplines, gives great hope for the creation of new drugs in which toxicological properties are reduced to a minimum, reduces the doses of medicines, offers targeted treatment and increases diagnostic possibilities. Nanotechnology is the source of a great revolution in medicine. It gives great hope for better and faster treatment of many diseases and gives hope for a better tomorrow. However, the creation of new "nanodrugs" requires a special understanding of the properties of nanoparticles. This article is a review work which determines and describes the way of creating new nanodrugs from ab initio calculations by docking and molecular dynamic applications up to a new medicinal product, as a proposal for the personalized medicine, in the early future. Nanomedicine ; Nanotechnology ; Applications of nanotechnology ; Drug delivery ; Engineering ethics ; Materials science ; Nanoparticle ; Engineering Fullerene Chemistry and Applications ; Carbon Nanotubes in Composites ; Graphene and Nanomaterials Applications
Authors: Farhad Gharagheizi | Poorandokht Ilani‐Kashkouli | Ronald C. Hedden
Source: Energy (article, 2018-05-31)
Field: Chemistry — Organic Chemistry

Standard molar chemical exergy: A new accurate model Standard molar entropy ; Enthalpy ; Molar ; Thermodynamics ; Chemistry ; Group contribution method ; Standard deviation ; Molar mass ; Standard enthalpy of formation ; Materials science ; Organic chemistry ; Mathematics ; Statistics Chemical Thermodynamics and Molecular Structure ; Phase Equilibria and Thermodynamics ; Process Optimization and Integration
Authors: Matilde de las Rivas | Earnest James Paul Daniel | Helena Coelho | Erandi Lira‐Navarrete | Lluı́s Raich | Ismael Compañón | Ana Diniz | Laura Lagartera | Jesús Jiménez‐Barbero | Henrik Clausen | Carme Rovira | Filipa Marcelo | Francisco Corzana | Thomas Gerken | Ramón Hurtado‐Guerrero
Source: ACS Central Science (article, 2018-09-14)
Field: Chemistry — Organic Chemistry

Structural and Mechanistic Insights into the Catalytic-Domain-Mediated Short-Range Glycosylation Preferences of GalNAc-T4 Mucin-type <i>O</i>-glycosylation is initiated by a family of polypeptide GalNAc-transferases (GalNAc-Ts) which are type-II transmembrane proteins that contain Golgi luminal catalytic and lectin domains that are connected by a flexible linker. Several GalNAc-Ts, including GalNAc-T4, show both long-range and short-range prior glycosylation specificity, governed by their lectin and catalytic domains, respectively. While the mechanism of the lectin-domain-dependent glycosylation is well-known, the molecular basis for the catalytic-domain-dependent glycosylation of glycopeptides is unclear. Herein, we report the crystal structure of GalNAc-T4 bound to the diglycopeptide GAT*GAGAGAGT*TPGPG (containing two α-GalNAc glycosylated Thr (T*), the PXP motif and a "naked" Thr acceptor site) that describes its catalytic domain glycopeptide GalNAc binding site. Kinetic studies of wild-type and GalNAc binding site mutant enzymes show the lectin domain GalNAc binding activity dominates over the catalytic domain GalNAc binding activity and that these activities can be independently eliminated. Surprisingly, a flexible loop protruding from the lectin domain was found essential for the optimal activity of the catalytic domain. This work provides the first structural basis for the short-range glycosylation preferences of a GalNAc-T. Glycosylation ; Domain (mathematical analysis) ; Catalysis ; Computational biology ; Range (aeronautics) ; Chemistry ; Computer science ; Biology ; Biochemistry ; Materials science Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Galectins and Cancer Biology
Authors: Xueqi Li | Selina C. Wang
Source: Journal of Food Quality (article, 2018-01-01)
Field: Chemistry — Organic Chemistry

Shelf Life of Extra Virgin Olive Oil and Its Prediction Models Extra virgin olive oil (EVOO), with high unsaturation degree (oleic acid, linoleic acid, and linolenic acid), is prone to oxidation during production and storage even with the presence of abundant antioxidants (e.g., phenolic compounds, alpha-tocopherol, and chlorophyll). The level of oxidation degradation is greatly affected by the EVOO chemical composition (free fatty acids, saturated and unsaturated fat ratio, total phenol content, etc.) and storage conditions (packaging material, oxygen, temperature, and light). With the increasing demand on qualitative acceptability and food safety of an EVOO product, consumers rely heavily on “shelf life” as a good indicator. Hence, it is critical for olive oil producers to provide accurate and practical information on shelf-life prediction. This review analyzes ten shelf-life prediction models that used various parameters and approaches for model establishment. Due to the complexity of chemical interactions between oil phase and environment under real-time storage and rapid accelerated testing conditions, further investigation is needed to scrutinize and minimize the discrepancies between real-time shelf life and predicted shelf life of EVOO products. Shelf life ; Degree of unsaturation ; Food science ; Oleic acid ; Olive oil ; Chemistry ; Linolenic acid ; Linoleic acid ; Lipid oxidation ; Fatty acid ; Biochemistry ; Organic chemistry ; Antioxidant Edible Oils Quality and Analysis ; Meat and Animal Product Quality ; Spectroscopy and Chemometric Analyses
Authors: Marcia Roy | Oksana Sorokina | C. Mclean | Silvia Tapia‐González | Javier DeFelipe | J. Douglas Armstrong | Seth G. N. Grant
Source: Proteomes (article, 2018-08-01)
Field: Chemistry — Spectroscopy

Regional Diversity in the Postsynaptic Proteome of the Mouse Brain The proteome of the postsynaptic terminal of excitatory synapses comprises over one thousand proteins in vertebrate species and plays a central role in behavior and brain disease. The brain is organized into anatomically distinct regions and whether the synapse proteome differs across these regions is poorly understood. Postsynaptic proteomes were isolated from seven forebrain and hindbrain regions in mice and their composition determined using proteomic mass spectrometry. Seventy-four percent of proteins showed differential expression and each region displayed a unique compositional signature. These signatures correlated with the anatomical divisions of the brain and their embryological origins. Biochemical pathways controlling plasticity and disease, protein interaction networks and individual proteins involved with cognition all showed differential regional expression. Combining proteomic and connectomic data shows that interconnected regions have specific proteome signatures. Diversity in synapse proteome composition is key feature of mouse and human brain structure. Proteome ; Postsynaptic potential ; Forebrain ; Postsynaptic density ; Biology ; Neuroscience ; Proteomics ; Synapse ; Excitatory postsynaptic potential ; Central nervous system ; Bioinformatics ; Genetics ; Inhibitory postsynaptic potential ; Receptor ; Gene Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Alzheimer's disease research and treatments
Authors: Wenyu Peng | Xuelian Gou | Hongling Qin | Meiyun Zhao | Xinze Zhao | Zhiguang Guo
Source: Applied Surface Science (article, 2018-10-04)
Field: Materials Science — Surfaces, Coatings and Films

Robust Mg(OH)2/epoxy resin superhydrophobic coating applied to composite insulators Epoxy ; Coating ; Stearic acid ; Materials science ; Composite material ; Composite number ; Superhydrophobic coating ; Durability ; Contact angle ; Surface roughness Surface Modification and Superhydrophobicity ; High voltage insulation and dielectric phenomena ; Aerogels and thermal insulation
Authors: Joonhee Kang | Seung Hyo Noh | Jeemin Hwang | Hoje Chun | Hansung Kim | Byungchan Han
Source: Physical Chemistry Chemical Physics (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

First-principles database driven computational neural network approach to the discovery of active ternary nanocatalysts for oxygen reduction reaction An elegant machine-learning-based algorithm was applied to study the thermo-electrochemical properties of ternary nanocatalysts for oxygen reduction reaction (ORR). High-dimensional neural network potentials (NNPs) for the interactions among the components were parameterized from big dataset established by first-principles density functional theory calculations. The NNPs were then incorporated with Monte Carlo (MC) and molecular dynamics (MD) simulations to identify not only active, but also electrochemically stable nanocatalysts for ORR in acidic solution. The effects of surface strain caused by selective segregation of certain components on the catalytic performance were accurately characterized. The computationally efficient and precise approach proposes a promising ORR candidate: 2.6 nm icosahedron comprising 60% of Pt and 40% Ni/Cu. Our methodology can be applied for high-throughput screening and designing of key functional nanomaterials to drastically enhance the performance of various electrochemical systems. Nanomaterial-based catalyst ; Ternary operation ; Reduction (mathematics) ; Oxygen reduction reaction ; Computer science ; Artificial neural network ; Chemistry ; Catalysis ; Database ; Artificial intelligence ; Mathematics ; Organic chemistry ; Physical chemistry Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Advanced Memory and Neural Computing
Authors: Kevin Tran | Aini Palizhati | Seoin Back | Zachary W. Ulissi
Source: Journal of Chemical Information and Modeling (article, 2018-11-19)
Field: Materials Science — Materials Chemistry

Dynamic Workflows for Routine Materials Discovery in Surface Science The rising application of informatics and data science tools for studying inorganic crystals and small molecules has revolutionized approaches to materials discovery and driven the development of accurate machine learning structure/property relationships. We discuss how informatics tools can accelerate research, and we present various combinations of workflows, databases, and surrogate models in the literature. This paradigm has been slower to infiltrate the catalysis community due to larger configuration spaces, difficulty in describing necessary calculations, and thermodynamic/kinetic quantities that require many interdependent calculations. We present our own informatics tool that uses dynamic dependency graphs to share, organize, and schedule calculations to enable new, flexible research workflows in surface science. This approach is illustrated for the large-scale screening of intermetallic surfaces for electrochemical catalyst activity. Similar approaches will be important to bring the benefits of informatics and data science to surface science research. Lastly, we provide our perspective on when to use these tools and considerations when creating them. Workflow ; Computer science ; Informatics ; Data science ; Materials informatics ; Interdependence ; Cheminformatics ; Health informatics ; Engineering informatics ; Bioinformatics ; Database ; Engineering Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; CO2 Reduction Techniques and Catalysts
Authors: Johannes T. Margraf | Karsten Reuter
Source: The Journal of Physical Chemistry A (article, 2018-07-09)
Field: Materials Science — Materials Chemistry

Making the Coupled Cluster Correlation Energy Machine-Learnable Calculating the electronic structure of molecules and solids has become an important pillar of modern research in diverse fields of research from biology and materials science to chemistry and physics. Unfortunately, increasingly accurate and thus reliable approximate solution schemes to the underlying Schrödinger equation scale steeply in computational cost, rendering most accurate approaches like "gold standard" coupled cluster theory, CC, quickly intractable for larger systems of interest. Here we show that this scaling can be significantly reduced by applying machine-learning to the CC correlation energy. We introduce a vector-based representation of CC wave functions and use potential energy surfaces of a small molecule test set to learn the correlation energy from this representation. Our results show that the CC correlation energy can be efficiently learned, even when the representation is constructed from approximate amplitudes provided by computationally less demanding Møller-Plesset (MP2) perturbation theory. Exploiting existing linear scaling MP2 implementations, this potentially opens the door to CC-quality molecular dynamics simulations. Coupled cluster ; Scaling ; Computer science ; Electronic correlation ; Rendering (computer graphics) ; Representation (politics) ; Statistical physics ; Correlation ; Linear scale ; Perturbation theory (quantum mechanics) ; Cluster (spacecraft) ; Computational science ; Theoretical computer science ; Physics ; Mathematics ; Artificial intelligence ; Quantum mechanics ; Molecule ; Geometry Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Spectroscopy and Quantum Chemical Studies
Authors: Gülşah Saydan Kanberoğlu | Erkan Yılmaz | Mustafa Soylak
Source: Microchemical Journal (article, 2018-11-28)
Field: Chemistry — Analytical Chemistry

Developing a new and simple ultrasound-assisted emulsification liquid phase microextraction method built upon deep eutectic solvents for Patent Blue V in syrup and water samples Chromatography ; Chemistry ; Choline chloride ; Detection limit ; Eutectic system ; Spectrophotometry ; Deep eutectic solvent ; Analytical Chemistry (journal) ; Organic chemistry Analytical chemistry methods development ; Dye analysis and toxicity ; Electrochemical Analysis and Applications
Authors: Samir Hanash | Edwin J. Ostrin | Johannes F. Fahrmann
Source: Translational Lung Cancer Research (review, 2018-06-01)
Field: Chemistry — Spectroscopy

Blood based biomarkers beyond genomics for lung cancer screening While there is considerable interest at the present time in the development of so-called liquid biopsy approaches for cancer detection based notably on circulating tumor DNA, there are other types of potential biomarkers that show promise for lung cancer screening and early detection. Here we review approaches and some of the promising markers based on proteomics, metabolomics and the immune response to tumor antigens in the form of autoantibodies. Liquid biopsy ; Lung cancer ; Proteomics ; Medicine ; Metabolomics ; Cancer ; Genomics ; Immune system ; Cancer biomarkers ; Computational biology ; Autoantibody ; Biomarker discovery ; Biomarker ; Circulating tumor cell ; Bioinformatics ; Immunology ; Genome ; Pathology ; Antibody ; Biology ; Internal medicine ; Gene ; Genetics ; Metastasis Advanced Proteomics Techniques and Applications ; RNA modifications and cancer ; Cancer Genomics and Diagnostics
Authors: Prashant Kumar Mishra | Rakesh Kumar | Pramod Kumar
Source: Nanoscale (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Surfactant-free one-pot synthesis of CeO<sub>2</sub>, TiO<sub>2</sub> and Ti@Ce oxide nanoparticles for the ultrafast removal of Cr(<scp>vi</scp>) from aqueous media Cerium oxide (CeO2), titanium oxide (TiO2) and titanium oxide impregnated with cerium oxide (Ti@Ce oxide) nanoparticles were synthesized using a simple one-pot surfactant-free method. The synthesized adsorbents were tested against the removal of Cr(vi) from aqueous medium. Comprehensive characterization methods like BET, XRD, SEM, EDAX, HR-TEM, SAED, HR-XPS and FT-IR were performed at different stages of the adsorption process and synthesis. A N2-BET study revealed the large surface area (268 m2 g-1) and pore size (6.8 nm) of CeO2 nanoparticles, which decreased after impregnation of titania. An XRD study demonstrated the phase transformation of TiO2 from the anatase phase to the rutile phase after the impregnation with CeO2 by lowering the phase transformation temperature from >550 °C to 400 °C. Ti0.3@Ce0.7 oxide nanoparticles showed 81% removal of Cr(vi) within 2.5 min of initiating the adsorption process while more than 92% removal of Cr(vi) was achieved within 10 min of adsorption. A HR-XPS study indicated the dual oxidation states of ceria and titania metals, which helped to convert the more toxic Cr(vi) ions to less toxic Cr(iii) ions during the adsorption process. The adsorption pattern depicted the monolayer behavior of Cr(vi) obeying the Redlich-Peterson isotherm and followed pseudo second-order kinetics. An intraparticle diffusion model disclosed the surface and pore resistance diffusion of Cr(vi) on the surface of adsorbents. Adsorption ; Cerium oxide ; Materials science ; X-ray photoelectron spectroscopy ; Anatase ; Oxide ; Aqueous solution ; Nanoparticle ; Cerium ; BET theory ; Titanium oxide ; Chemical engineering ; Langmuir adsorption model ; Inorganic chemistry ; Nuclear chemistry ; Chemistry ; Nanotechnology ; Photocatalysis ; Catalysis ; Organic chemistry ; Metallurgy Advanced Nanomaterials in Catalysis ; Advanced Photocatalysis Techniques ; Nanomaterials for catalytic reactions
Authors: Mattia Silvi | Raffael Schrof | Adam Noble | Varinder K. Aggarwal
Source: Chemistry - A European Journal (article, 2018-02-07)
Field: Chemistry — Organic Chemistry

Enantiospecific Three‐Component Alkylation of Furan and Indole Furan- and indole-derived boronate complexes react with alkyl iodides under radical (photoredox) or polar (S<sub>N</sub> 2) conditions to generate three-component alkylation products with high efficiency and complete stereospecificity. The methodology allows the incorporation of versatile functional groups such as nitriles, ketones, esters, sulfones, and amides, providing rapid access to complex chiral heteroaromatic molecules in enantioenriched form. Interestingly, while indolyl boronate complexes react directly with alkyl halides in a polar pathway, furyl boronates require photoredox catalysis. Careful mechanistic analysis revealed that the boronate complex not only serves as a substrate in the reaction but also acts as a reductive quencher for the excited state of the photocatalyst. Furan ; Alkylation ; Indole test ; Component (thermodynamics) ; Chemistry ; Stereochemistry ; Organic chemistry ; Catalysis ; Physics Oxidative Organic Chemistry Reactions ; Radical Photochemical Reactions ; Asymmetric Synthesis and Catalysis
Authors: Mingfu He | Youho Lee
Source: Nuclear Engineering and Design (article, 2018-08-25)
Field: Materials Science — Materials Chemistry

Application of machine learning for prediction of critical heat flux: Support vector machine for data-driven CHF look-up table construction based on sparingly distributed training data points Support vector machine ; Data point ; Extrapolation ; Parametric statistics ; Computer science ; Table (database) ; Inflection point ; Data mining ; Critical heat flux ; Machine learning ; Artificial intelligence ; Heat flux ; Heat transfer ; Mathematics ; Mechanics ; Physics Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Nuclear Engineering Thermal-Hydraulics