jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: L. De Smet | Gertjan Vancoillie | Peter Minshall | Kathleen Lava | Iline Steyaert | Ella Schoolaert | Elke Van De Walle | Peter Dubruel | Karen De Clerck | Richard Hoogenboom
Source: Nature Communications (article, 2018-03-12)
Field: Materials Science — Materials Chemistry

Plasma dye coating as straightforward and widely applicable procedure for dye immobilization on polymeric materials Here, we introduce a novel concept for the fabrication of colored materials with significantly reduced dye leaching through covalent immobilization of the desired dye using plasma-generated surface radicals. This plasma dye coating (PDC) procedure immobilizes a pre-adsorbed layer of a dye functionalized with a radical sensitive group on the surface through radical addition caused by a short plasma treatment. The non-specific nature of the plasma-generated surface radicals allows for a wide variety of dyes including azobenzenes and sulfonphthaleins, functionalized with radical sensitive groups to avoid significant dye degradation, to be combined with various materials including PP, PE, PA6, cellulose, and PTFE. The wide applicability, low consumption of dye, relatively short procedure time, and the possibility of continuous PDC using an atmospheric plasma reactor make this procedure economically interesting for various applications ranging from simple coloring of a material to the fabrication of chromic sensor fabrics as demonstrated by preparing a range of halochromic materials. Radical ; Coating ; Adsorption ; Chemical engineering ; Fabrication ; Cellulose ; Covalent bond ; Materials science ; Plasma ; Chemistry ; Photochemistry ; Nanotechnology ; Organic chemistry Luminescence and Fluorescent Materials ; Advanced Sensor and Energy Harvesting Materials ; Conducting polymers and applications
Authors: Xiaoming Wang | Xingeng Li | Qingquan Lei | Yaping Wu | Wenjing Li
Source: Royal Society Open Science (article, 2018-07-01)
Field: Materials Science — Surfaces, Coatings and Films

Fabrication of superhydrophobic composite coating based on fluorosilicone resin and silica nanoparticles Composite superhydrophobic coating built with film former and filler is attracting much attention for its facile and convenient fabrication, but significant limitations and disadvantages still remain. In this paper, a composite superhydrophobic coating is introduced which can be cured at room temperature and made by dispersing modified silica nanoparticles with 1H, 1H, 2H, 2H-perfluorooctyltriethoxysilane in fluorosilicone resin. Silica content and dispersion time showed obvious influences on the morphology and topography of composite coating by reuniting dispersed nanoparticles to form peaks on the surface. Excessively large distances between these peaks would decrease water contact angle value. Increasing slope of peaks, appropriate distance between peaks and decreasing diameter size of peaks would diminish sliding angle value. Formation mechanism of the composite coating based on fluorosilicone resin and modified nanoparticles was explained using interpenetrating polymer model. Materials science ; Coating ; Composite number ; Fabrication ; Contact angle ; Composite material ; Nanoparticle ; Polymer ; Dispersion (optics) ; Superhydrophobic coating ; Nanotechnology ; Optics Surface Modification and Superhydrophobicity ; High voltage insulation and dielectric phenomena ; Aerogels and thermal insulation
Authors: Pan Zhang | Lin Shen | Weitao Yang
Source: The Journal of Physical Chemistry B (article, 2018-12-17)
Field: Materials Science — Materials Chemistry

Solvation Free Energy Calculations with Quantum Mechanics/Molecular Mechanics and Machine Learning Models For exploration of chemical and biological systems, the combined quantum mechanics and molecular mechanics (QM/MM) and machine learning (ML) models have been developed recently to achieve high accuracy and efficiency for molecular dynamics (MD) simulations. Despite its success on reaction free energy calculations, how to identify new configurations on insufficiently sampled regions during MD and how to update the current ML models with the growing database on the fly are both very important but still challenging. In this article, we apply the QM/MM ML method to solvation free energy calculations and address these two challenges. We employ three approaches to detect new data points and introduce the gradient boosting algorithm to reoptimize efficiently the ML model during ML-based MD sampling. The solvation free energy calculations on several typical organic molecules demonstrate that our developed method provides a systematic, robust, and efficient way to explore new chemistry using ML-based QM/MM MD simulations. Solvation ; Molecular mechanics ; Molecular dynamics ; Statistical physics ; Computer science ; Implicit solvation ; Energy (signal processing) ; Chemistry ; Physics ; Molecule ; Computational chemistry ; Quantum mechanics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Laurie J. Points | James W. Taylor | Jonathan Grizou | Kevin Donkers | Leroy Cronin
Source: Proceedings of the National Academy of Sciences (article, 2018-01-16)
Field: Materials Science — Materials Chemistry

Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior Protocell models are used to investigate how cells might have first assembled on Earth. Some, like oil-in-water droplets, can be seemingly simple models, while able to exhibit complex and unpredictable behaviors. How such simple oil-in-water systems can come together to yield complex and life-like behaviors remains a key question. Herein, we illustrate how the combination of automated experimentation and image processing, physicochemical analysis, and machine learning allows significant advances to be made in understanding the driving forces behind oil-in-water droplet behaviors. Utilizing >7,000 experiments collected using an autonomous robotic platform, we illustrate how smart automation cannot only help with exploration, optimization, and discovery of new behaviors, but can also be core to developing fundamental understanding of such systems. Using this process, we were able to relate droplet formulation to behavior via predicted physical properties, and to identify and predict more occurrences of a rare collective droplet behavior, droplet swarming. Proton NMR spectroscopic and qualitative pH methods enabled us to better understand oil dissolution, chemical change, phase transitions, and droplet and aqueous phase flows, illustrating the utility of the combination of smart-automation and traditional analytical chemistry techniques. We further extended our study for the simultaneous exploration of both the oil and aqueous phases using a robotic platform. Overall, this work shows that the combination of chemistry, robotics, and artificial intelligence enables discovery, prediction, and mechanistic understanding in ways that no one approach could achieve alone. Protocell ; Collective behavior ; Automation ; Artificial intelligence ; Computer science ; Process (computing) ; Robotics ; Nanotechnology ; Biochemical engineering ; Chemistry ; Engineering ; Materials science ; Robot ; Mechanical engineering Machine Learning in Materials Science ; Micro and Nano Robotics ; Spectroscopy and Quantum Chemical Studies
Authors: Jiajia Yang | Yun Li | Chaonan Huang | Yanna Jiao | Jiping Chen
Source: Polymers (article, 2018-10-15)
Field: Chemistry — Analytical Chemistry

A Phenolphthalein-Dummy Template Molecularly Imprinted Polymer for Highly Selective Extraction and Clean-Up of Bisphenol A in Complex Biological, Environmental and Food Samples A molecularly imprinted polymer (MIP) for highly selective solid-phase extraction (SPE) of bisphenol A (BPA) was prepared using phenolphthalein (PP) as the novel dummy template by bulk polymerization. A particle diameter distribution of 40⁻60 μm, a specific surface area of 359.8 m²·g<sup>-1</sup>, and a total pore volume of 0.730 cm³·g<sup>-1</sup> for the prepared PP-imprinted polymer (PPMIP) were obtained. Good selectivity and specific adsorption capacity for BPA of the prepared PPMIP were also demonstrated by the chromatographic evaluation and sorption experiments. The PPMIP as a SPE sorbent was evaluated for the selective extraction and clean-up of BPA from complex biological, environmental, and food samples. Meanwhile, an accurate and sensitive analytical method based on the PPMIP-SPE purification procedure coupled with high performance liquid chromatography-diode array detector (HPLC-DAD) detection has been successfully developed for the rapid determination of BPA from these samples, with detection limits of 1.3 ng·mL<sup>-1</sup> for bovine serum and milk, 2.6 ng·mL<sup>-1</sup> for human urine and edible oil, 5.2 ng·mL<sup>-1</sup> for soybean sauce, and 1.3 ng·g<sup>-1</sup> for sediment. The BPA recoveries at two different spiking levels were in the range of 82.1⁻106.9%, with relative standard deviation (RSD) values below 7.7%. Molecularly imprinted polymer ; Chromatography ; Solid phase extraction ; Sorbent ; Extraction (chemistry) ; Bisphenol A ; Detection limit ; Chemistry ; Sorption ; Adsorption ; Phenolphthalein ; Polymer ; High-performance liquid chromatography ; Selectivity ; Organic chemistry Analytical chemistry methods development ; Effects and risks of endocrine disrupting chemicals ; Toxic Organic Pollutants Impact
Authors: Jino Mathew | David Parfitt | K. Wilford | Nick Riddle | Miltiadis Alamaniotis | A. Chroneos | Michael E. Fitzpatrick
Source: Journal of Nuclear Materials (article, 2018-02-21)
Field: Materials Science — Materials Chemistry

Reactor pressure vessel embrittlement: Insights from neural network modelling Embrittlement ; Artificial neural network ; Reactor pressure vessel ; Pressure vessel ; Nuclear engineering ; Irradiation ; Materials science ; Light-water reactor ; Computer science ; Artificial intelligence ; Nuclear physics ; Metallurgy ; Physics ; Engineering ; Composite material Nuclear Materials and Properties ; Fusion materials and technologies ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Rajiv Borah | Ganesh Ingavle | Susan Sandeman | Ashok Kumar | Sergey V. Mikhalovsky
Source: Biomaterials Science (article, 2018-01-01)
Field: Materials Science — Polymers and Plastics

Electrically conductive MEH-PPV:PCL electrospun nanofibres for electrical stimulation of rat PC12 pheochromocytoma cells The purpose of this study was to prepare an electrically conducting poly[2-methoxy-5-(2-ethyl-hexyloxy)-1,4-phenylene vinylene] (MEH-PPV) based nanofibrous scaffold and to investigate the synergetic effect of nanofibre structure and electrical stimulation on neuronal growth for possible use in nerve repair. Nanofibres were produced by electrospinning of blended MEH-PPV with polycaprolactone (PCL) at a ratio of 20 : 80, 40 : 60, 50 : 50 and 60 : 40 (v/v). A better electrical conductivity was achieved by using core-sheath structured nanofibres of PCL (core) and MEH-PPV (sheath) produced using the coaxial electrospinning technique. The highest electrical conductivity was observed in the core-sheath nanofibres, while it increased with increasing concentration of MEH-PPV for the blended electrospun nanofibres. The biocompatibility of the electrospun nanofibres was confirmed by MTS and live-dead staining assays using 3T3 fibroblasts and a neuronal rat pheochromocytoma (PC12) cell line. Beta (III) tubulin immunochemistry showed that PC12 cells differentiated into sympathetic neurons on these porous and stiffer electrospun nanofibres coated with collagen I. Improved cell morphology and attachment on the collagen I coated electrospun meshes has been confirmed by SEM analysis. Significant enhancement in neurite formation and neurite outgrowth of PC12 cells on the conductive scaffolds under electrical potential of 500 mV cm-1 for 2 h day-1 suggests the potential use of these scaffolds for nerve repair. Neurite ; Materials science ; Electrical conductor ; Stimulation ; Electrically conductive ; Biophysics ; Chemistry ; Composite material ; In vitro ; Medicine Conducting polymers and applications ; Electrospun Nanofibers in Biomedical Applications ; Advanced Sensor and Energy Harvesting Materials
Authors: David A. Armstrong | Quentin Kaas | K. Johan Rosengren
Source: Chemical Science (article, 2018-01-01)
Field: Chemistry — Spectroscopy

Prediction of disulfide dihedral angles using chemical shifts Cystine residues result from the formation of disulfide bonds between pairs of cysteine residues. This cross linking of the backbone is essential for the structure and activity of peptides and proteins. The conformation of a cystine side chain can be described using five dihedral angles, <i>χ</i>1, <i>χ</i>2, <i>χ</i>3, <i>χ</i>2', and <i>χ</i>1', with cystines favouring certain combinations of these angles. 2D NMR spectroscopy is ideally suited for structure determination of disulfide-rich peptides, because of their small size and constrained nature. However, only limited information of the cystine side chain conformation can be determined by NMR spectroscopy, leading to ambiguity in the deduced 3D structures. Resolving accurate structures is important as disulfide-rich peptides have proven to be promising drug candidates in a number of fields, either as bioactive leads or scaffolds. Using a database of NMR chemical shifts combined with crystallographic structures, we have developed a method called DISH that uses support vector machines to predict the dihedral angles of cysteine side chains. It is able to successfully predict <i>χ</i>2 angles with 91% accuracy, and has improved performance over existing prediction methods for <i>χ</i>1 angles, with 87% accuracy. For 81% of cysteine residues, DISH successfully predicted both the <i>χ</i>1 and <i>χ</i>2 angles. By revisiting published solution structures of peptides determined using NMR spectroscopy, we assessed the impact of additional cystine dihedral restraints on the quality of 3D models. DISH improved the resolution and accuracy, highlighting the potential for improving the understanding of structure-activity relationships and rational development of peptide drugs. Dihedral angle ; Disulfide bond ; Chemistry ; Crystallography ; Organic chemistry ; Molecule ; Biochemistry ; Hydrogen bond Molecular spectroscopy and chirality ; Computational Drug Discovery Methods ; Analytical Chemistry and Chromatography
Authors: Şule Yılmaz | Genet A. Shiferaw | Josep Rayó | Anastassios Economou | Lennart Martens | Elien Vandermarliere
Source: Mass Spectrometry Reviews (review, 2018-03-12)
Field: Chemistry — Spectroscopy

Cross‐linked peptide identification: A computational forest of algorithms Chemical cross-linking analyzed by mass spectrometry (XL-MS) has become an important tool in unravelling protein structure, dynamics, and complex formation. Because the analysis of cross-linked proteins with mass spectrometry results in specific computational challenges, many computational tools have been developed to identify cross-linked peptides from mass spectra and subsequently interpret the identified cross-links within their structural context. In this review, we will provide an overview of the different tools that are currently available to tackle the computational part of an XL-MS experiment. First, we give an introduction on the computational challenges encountered when processing data from a cross-linking experiment. We then discuss available tools to identify peptides that are linked by intact or MS-cleavable cross-linkers, and we provide an overview of tools to interpret cross-linked peptides in the context of protein structure. Finally, we give an outlook on data management and dissemination challenges and opportunities for cross-linking experiments. Context (archaeology) ; Chemistry ; Identification (biology) ; Mass spectrometry ; Computational biology ; Computer science ; Data science ; Chromatography Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Jawahar Khetan | Md Shahinuzzaman | Sutapa Barua | Dipak Barua
Source: Biophysical Journal (article, 2018-12-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Quantitative Analysis of the Correlation between Cell Size and Cellular Uptake of Particles Internalization ; Endocytic cycle ; Biophysics ; Extracellular ; Cell size ; Diffusion ; Endocytosis ; Cell ; Chemistry ; Particle size ; Vacuole ; Cell biology ; Nanotechnology ; Biology ; Materials science ; Physics ; Biochemistry ; Cytoplasm Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Nanoparticle-Based Drug Delivery
Authors: Siji Chen | Shanshan Tang | Yang Sun | Gang Wang | Huan Chen | Xiaoxiao Yu | Yingjie Su | Guang Chen
Source: Materials (article, 2018-08-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Preparation of a Highly Porous Carbon Material Based on Quinoa Husk and Its Application for Removal of Dyes by Adsorption A porous carbon material was prepared from quinoa husk (QH) by carbonization and chemical activation with KOH. A series of experiments, including SEM (Scanning electron microscopy), FT-IR (Fourier transform infrared), XRD (X-ray diffraction), Raman, X-ray photoelectron spectroscopy (XPS), and N₂ adsorption/desorption, were carried out on the porous carbon produced from quinoa husk (PC⁻QH). The results showed that PC⁻QH was mainly composed of activated carbon and graphite. Moreover, PC⁻QH exhibited a high level of porosity with a BET (the Brunauer⁻Emmett⁻Teller theory) surface area of 1713 m² g<sup>-1</sup>. As a representative dye, malachite green (MG) was selected to evaluate the performance of PC⁻QH to absorb the contaminants in dyeing wastewater. In batch adsorption experiments, PC⁻QH exhibited a high adsorption rate toward malachite green (MG). An uptake capacity of 599.90 mg g<sup>-1</sup> was achieved in the initial 5 min, and the MG adsorption capacity of PC⁻QH reached 1365.10 mg g<sup>-1</sup>, which was higher than many other adsorbents. The adsorption data were well fitted with the Freundlich isotherm model and the pseudo-second-order kinetic model. PC⁻QH also displayed a high absorption rate to rhodamine B (RhB), methyl violet (MV), methylene blue (MB), and methyl orange (MO). The results in this study suggest that PC⁻QH can be a promising adsorbent for quick treatment of dyeing wastewater. Husk ; Adsorption ; Porosity ; Carbon fibers ; Materials science ; Chemical engineering ; Pulp and paper industry ; Waste management ; Composite material ; Chemistry ; Organic chemistry ; Composite number ; Botany ; Engineering Supercapacitor Materials and Fabrication ; Adsorption and biosorption for pollutant removal ; Carbon Nanotubes in Composites
Authors: Wei Wen | Laurent Capolungo | C.N. Tomé
Source: International Journal of Plasticity (article, 2018-03-18)
Field: Materials Science — Materials Chemistry

Mechanism-based modeling of solute strengthening: Application to thermal creep in Zr alloy Creep ; Materials science ; Constitutive equation ; Dislocation ; Dislocation creep ; Hardening (computing) ; Work (physics) ; Diffusion creep ; Alloy ; Cladding (metalworking) ; Thermodynamics ; Work hardening ; Zirconium alloy ; Mechanics ; Composite material ; Microstructure ; Finite element method ; Grain boundary ; Layer (electronics) Nuclear Materials and Properties ; Microstructure and mechanical properties ; High Temperature Alloys and Creep
Authors: Dejiang Zhang | Lande Liu | Shijie Xu | Shichao Du | Weibing Dong | Junbo Gong
Source: Journal of Crystal Growth (article, 2018-01-03)
Field: Materials Science — Materials Chemistry

Optimization of cooling strategy and seeding by FBRM analysis of batch crystallization Seeding ; Crystallization ; Nucleation ; Trajectory ; Biological system ; Constant (computer programming) ; Process (computing) ; Materials science ; Beam (structure) ; Optics ; Physics ; Computer science ; Thermodynamics ; Biology Crystallization and Solubility Studies ; Freezing and Crystallization Processes
Authors: Ziqing Lin | Liming Wei | Wenxuan Cai | Yanlong Zhu | Trisha Tucholski | Stanford D. Mitchell | Wei Guo | Stephen P. Ford | Gary M. Diffee | Ying Ge
Source: Molecular & Cellular Proteomics (article, 2018-12-27)
Field: Chemistry — Spectroscopy

Simultaneous Quantification of Protein Expression and Modifications by Top-down Targeted Proteomics: A Case of the Sarcomeric Subproteome Determining changes in protein expression and post-translational modifications (PTMs) is crucial for elucidating cellular signal transduction and disease mechanisms. Conventional antibody-based approaches have inherent problems such as the limited availability of high-quality antibodies and batch-to-batch variation. Top-down mass spectrometry (MS)-based proteomics has emerged as the most powerful method for characterization and quantification of protein modifications. Nevertheless, robust methods to simultaneously determine changes in protein expression and PTMs remain lacking. Herein, we have developed a straightforward and robust top-down liquid chromatography (LC)/MS-based targeted proteomics platform for simultaneous quantification of protein expression and PTMs with high throughput and high reproducibility. We employed this method to analyze the sarcomeric subproteome from various muscle types of different species, which successfully revealed skeletal muscle heterogeneity and cardiac developmental changes in sarcomeric protein isoform expression and PTMs. As demonstrated, this targeted top-down proteomics platform offers an excellent 'antibody-independent' alternative for the accurate quantification of sarcomeric protein expression and PTMs concurrently in complex mixtures, which is generally applicable to different species and various tissue types. Proteomics ; Computational biology ; Quantitative proteomics ; Protein expression ; Proteome ; Chemistry ; Signal transduction ; Posttranslational modification ; Label-free quantification ; Bioinformatics ; Biology ; Biochemistry ; Enzyme Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications
Authors: Achraf Noureddine | C. Jeffrey Brinker
Source: Chemical Engineering Journal (article, 2018-02-02)
Field: Materials Science — Materials Chemistry

Pendant/bridged/mesoporous silsesquioxane nanoparticles: Versatile and biocompatible platforms for smart delivery of therapeutics Silsesquioxane ; Nanoparticle ; Nanotechnology ; Drug delivery ; Mesoporous material ; Materials science ; Biocompatible material ; Mesoporous silica ; Chemistry ; Organic chemistry ; Polymer ; Catalysis ; Biomedical engineering Silicone and Siloxane Chemistry ; Mesoporous Materials and Catalysis ; Surface Modification and Superhydrophobicity
Authors: M.H. Jalaei | A. Ghorbanpour Arani | H. Tourang
Source: International Journal of Engineering Science (article, 2018-08-04)
Field: Materials Science — Materials Chemistry

On the dynamic stability of viscoelastic graphene sheets Viscoelasticity ; Boundary value problem ; Orthotropic material ; Mechanics ; Dimensionless quantity ; Materials science ; Dissipation ; Equations of motion ; Stiffness ; Hamilton's principle ; Aspect ratio (aeronautics) ; Ritz method ; Classical mechanics ; Mathematical analysis ; Physics ; Mathematics ; Composite material ; Finite element method Nonlocal and gradient elasticity in micro/nano structures ; Numerical methods in engineering ; Composite Structure Analysis and Optimization