jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ella Schoolaert | Luisa Cossu | Jana Becelaere | Joachim F. R. Van Guyse | Ali Tigrine | Maarten Vergaelen | Richard Hoogenboom | Karen De Clerck
Source: Materials & Design (article, 2020-04-24)
Field: Materials Science — Biomaterials

Nanofibers with a tunable wettability by electrospinning and physical crosslinking of poly(2-n-propyl-2-oxazoline) This work shows the design of highly porous membranes with tunable wettability based on poly(2-n-propyl-2-oxazoline) (PnPrOx) nanofibers. Wicking and advanced contact angle experiments demonstrate the high potential for applications requiring specific interactions with aqueous media. PnPrOx is a popular member among the biocompatible poly(2-oxazoline)s due to its thermoresponsiveness in aqueous solutions, enabling the production of ‘smart materials’. On material level, however, many interesting properties of this polymer remain undiscovered. Electrospinning is an ideal technique to transfer the properties observed in solutions to end-material properties, as the polymer is processed into highly porous, nanofibrous membranes. PnPrOx' electrospinnability is here investigated in environmentally friendly ethanol/water solvent systems, ensuring industrial scalability. The nanofibrous membranes show increased hydrophobicity exhibiting the rose-petal effect. Upon functionalization with tannic acid, the hydrophobic membranes are transformed into hydrophilic nanofibers showing water-stability in both fresh and salty water, even below the polymer cloud point temperature. By varying the tannic acid amount, the hydrophilicity can be fine-tuned as the contact area between water droplets and surface, the rate and manner of water uptake and the extent of the rose-petal effect can be manipulated easily. Hence an interesting material is designed for applications in which water caption and transport are important. Materials science ; Contact angle ; Chemical engineering ; Nanofiber ; Membrane ; Wetting ; Electrospinning ; Polymer ; Aqueous solution ; Surface modification ; Tannic acid ; Polymer chemistry ; Nanotechnology ; Composite material ; Organic chemistry ; Chemistry Electrospun Nanofibers in Biomedical Applications ; Surface Modification and Superhydrophobicity ; Advanced Sensor and Energy Harvesting Materials
Authors: William A. Golding | Hendrik L. Schmitt | Robert J. Phipps
Source: Journal of the American Chemical Society (article, 2020-12-17)
Field: Chemistry — Organic Chemistry

Systematic Variation of Ligand and Cation Parameters Enables Site-Selective C–C and C–N Cross-Coupling of Multiply Chlorinated Arenes through Substrate–Ligand Electrostatic Interactions Use of attractive noncovalent interactions between ligand and substrate is an emerging strategy for controlling positional selectivity. A key question relates to whether fine control on molecules with multiple, closely spaced reactive positions is achievable using typically less directional electrostatic interactions. Herein, we apply a 10-piece "toolkit" comprising of two closely related sulfonated phosphine ligands and five bases, each possessing varying cation size, to the challenge of site-selective cross-coupling of multiply chlorinated arenes. The fine tuning provided by these ligand/base combinations is effective for Suzuki-Miyaura coupling and Buchwald-Hartwig coupling on a range of isomeric dichlorinated and trichlorinated arenes, substrates that would produce intractable mixtures when typical ligands are used. This study develops a practical solution for site-selective cross-coupling to generate complex, highly substituted arenes. Chemistry ; Ligand (biochemistry) ; Substrate (aquarium) ; Coupling (piping) ; Phosphine ; Selectivity ; Electrostatics ; Combinatorial chemistry ; Non-covalent interactions ; Computational chemistry ; Molecule ; Stereochemistry ; Chemical physics ; Organic chemistry ; Physical chemistry ; Hydrogen bond ; Catalysis Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Radical Photochemical Reactions
Authors: Pavel Padnya | Vladimir V. Gorbachuk | Ivan I. Stoikov
Source: International Journal of Molecular Sciences (review, 2020-02-20)
Field: Chemistry — Spectroscopy

The Role of Calix[n]arenes and Pillar[n]arenes in the Design of Silver Nanoparticles: Self-Assembly and Application Silver nanoparticles (AgNPs) are an attractive alternative to plasmonic gold nanoparticles. The relative cheapness and redox stability determine the growing interest of researchers in obtaining selective plasmonic and electrochemical (bio)sensors based on silver nanoparticles. The controlled synthesis of metal nanoparticles of a defined morphology is a nontrivial task, important for such fields as biochemistry, catalysis, biosensors and microelectronics. Cyclophanes are well known for their great receptor properties and are of particular interest in the creation of metal nanoparticles due to a variety of cyclophane 3D structures and unique redox abilities. Silver ion-based supramolecular assemblies are attractive due to the possibility of reduction by "soft" reducing agents as well as being accessible precursors for silver nanoparticles of predefined morphology, which are promising for implementation in plasmonic sensors. For this purpose, the chemistry of cyclophanes offers a whole arsenal of approaches: exocyclic ion coordination, association, stabilization of the growth centers of metal nanoparticles, as well as in reduction of silver ions. Thus, this review presents the recent advances in the synthesis and stabilization of Ag (0) nanoparticles based on self-assembly of associates with Ag (I) ions with the participation of bulk platforms of cyclophanes (resorcin[4]arenes, (thia)calix[n]arenes, pillar[n]arenes). Nanoparticle ; Silver nanoparticle ; Supramolecular chemistry ; Nanotechnology ; Redox ; Plasmonic nanoparticles ; Chemistry ; Metal ions in aqueous solution ; Combinatorial chemistry ; Plasmon ; Cyclophane ; Calixarene ; Electrochemistry ; Metal ; Materials science ; Organic chemistry ; Molecule ; Electrode ; Physical chemistry Molecular Sensors and Ion Detection ; Supramolecular Chemistry and Complexes ; Nanocluster Synthesis and Applications
Authors: Sascha Keller | Mako Kamiya | Yasuteru Urano
Source: Molecules (review, 2020-12-16)
Field: Materials Science — Materials Chemistry

Recent Progress in Small Spirocyclic, Xanthene-Based Fluorescent Probes The use of fluorescent probes in a multitude of applications is still an expanding field. This review covers the recent progress made in small molecular, spirocyclic xanthene-based probes containing different heteroatoms (e.g., oxygen, silicon, carbon) in position 10'. After a short introduction, we will focus on applications like the interaction of probes with enzymes and targeted labeling of organelles and proteins, detection of small molecules, as well as their use in therapeutics or diagnostics and super-resolution microscopy. Furthermore, the last part will summarize recent advances in the synthesis and understanding of their structure-behavior relationship including novel computational approaches. Xanthene ; Nanotechnology ; Heteroatom ; Chemistry ; Fluorescence ; Small molecule ; Materials science ; Biochemistry ; Organic chemistry ; Physics Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Photochromic and Fluorescence Chemistry
Authors: Izabela Malinowska | Zuzanna Ryżyńska | Eryka Mrotek | Tomasz Klimczuk | Anna Zielińska‐Jurek
Source: Journal of Nanomaterials (article, 2020-05-05)
Field: Materials Science — Materials Chemistry

Synthesis of CoFe<sub>2</sub>O<sub>4</sub> Nanoparticles: The Effect of Ionic Strength, Concentration, and Precursor Type on Morphology and Magnetic Properties The present study highlights the effect of metal precursor types (SO 4 2 ¯, Cl¯, and NO 3 ¯), their concentration, and the influence of ionic strength of reaction environment on the morphology, surface, and magnetic properties of CoFe 2 O 4 particles. The magnetic nanoparticles were obtained by chemical coprecipitation in alkaline medium at increasing metal concentration in the range of 0.0425 mol·dm -3 to 0.17 mol·dm -3 and calcination temperature from 400°C to 800°C. It was found that the chemistry of precursors can be directly correlated with magnetic properties. The CoFe 2 O 4 particles from metal sulphate precursors showed the highest saturation magnetization and the lowest coercivity. The adjustment of ionic strength in the range of 1.25–5 M was achieved by adding an appropriate quantity of metal sulphates into aqueous solutions at a constant pH or by adding an appropriate quantity of NaClO 5 under similar conditions. The average hydrodynamic size of CoFe 2 O 4 increased from 46 nm to 54 nm with increasing metal concentration and ionic strength. An explanation of magnetic properties, caused by ionic strength and metal concentration, is given based mainly on the reduction in repulsive forces at the particle interface and compensation of the double electric layer in the presence of anions. The observed coercivity was lower for the particles obtained in solutions with the highest ionic strength, whereas the concentration of metals and calcination temperature affected the saturation magnetization and morphology of the obtained cobalt ferrite particles. Ionic strength ; Materials science ; Coercivity ; Coprecipitation ; Calcination ; Metal ; Particle size ; Aqueous solution ; Nanoparticle ; Ionic bonding ; Saturation (graph theory) ; Magnetic nanoparticles ; Chemical engineering ; Analytical Chemistry (journal) ; Inorganic chemistry ; Metallurgy ; Nanotechnology ; Ion ; Chemistry ; Physical chemistry ; Catalysis ; Chromatography Magnetic Properties and Synthesis of Ferrites ; Iron oxide chemistry and applications ; Multiferroics and related materials
Authors: Lorenz Lindenthal | Raffael Rameshan | Harald Summerer | Thomas Ruh | Janko Popovic | Andreas Nenning | Stefan Löffler | Alexander Karl Opitz | Peter Blaha | Christoph Rameshan
Source: Catalysts (article, 2020-03-01)
Field: Materials Science — Materials Chemistry

Modifying the Surface Structure of Perovskite-Based Catalysts by Nanoparticle Exsolution In heterogeneous catalysis, surfaces decorated with uniformly dispersed, catalytically-active (nano)particles are a key requirement for excellent performance. Beside standard catalyst preparation routines—with limitations in controlling catalyst surface structure (i.e., particle size distribution or dispersion)—we present here a novel time efficient route to precisely tailor catalyst surface morphology and composition of perovskites. Perovskite-type oxides of nominal composition ABO3 with transition metal cations on the B-site can exsolve the B-site transition metal upon controlled reduction. In this exsolution process, the transition metal emerges from the oxide lattice and migrates to the surface where it forms catalytically active nanoparticles. Doping the B-site with reducible and catalytically highly active elements, offers the opportunity of tailoring properties of exsolution catalysts. Here, we present the synthesis of two novel perovskite catalysts Nd0.6Ca0.4FeO3-δ and Nd0.6Ca0.4Fe0.9Co0.1O3-δ with characterisation by (in situ) XRD, SEM/TEM and XPS, supported by theory (DFT+U). Fe nanoparticle formation was observed for Nd0.6Ca0.4FeO3-δ. In comparison, B site cobalt doping leads, already at lower reduction temperatures, to formation of finely dispersed Co nanoparticles on the surface. These novel perovskite-type catalysts are highly promising for applications in chemical energy conversion. First measurements revealed that exsolved Co nanoparticles significantly improve the catalytic activity for CO2 activation via reverse water gas shift reaction. Catalysis ; Nanoparticle ; Materials science ; Chemical engineering ; Transition metal ; Perovskite (structure) ; Metal ; X-ray photoelectron spectroscopy ; Specific surface area ; Oxide ; Dispersion (optics) ; Nanotechnology ; Inorganic chemistry ; Chemistry ; Metallurgy Catalytic Processes in Materials Science ; Magnetic and transport properties of perovskites and related materials ; Advancements in Solid Oxide Fuel Cells
Authors: Zhongxu Lian | Jinkai Xu | Zuobin Wang | Huadong Yu
Source: Journal of Bionic Engineering (article, 2020-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Biomimetic Superlyophobic Metallic Surfaces: Focusing on Their Fabrication and Applications Abstract Metals are indispensable engineered materials for day-to-day life. Researches focused on metallic surfaces with superlyophobicity (superhydrophobicity, superoleophobicity, underwater superoleophobicity and slippery characteristic) have attracted much attention recently. Nature is a magician that gives each organic life a unique advantage. Researchers have created a large number of biomimetic superlyophobic metallic surfaces through various approaches. These biomimetic superlyophobic metallic surfaces exhibit advantages in many applications, such as self-cleaning, corrosion resistance, anti-icing, and drag reduction. In this review, the specific fabrication and applications of biomimetic superlyophobic metallic surfaces were reported. The remaining challenges and future outlook of biomimetic superlyophobic metallic surfaces were preliminarily analyzed. It is hoped that the review will be essential for broadening the scope of potential applications of metals and providing a powerful reference for future research on metal-based advanced functional materials. Nanotechnology ; Materials science ; Fabrication ; Biomimetic materials ; Biomimetics ; Metal ; Corrosion ; Scope (computer science) ; Metallurgy ; Computer science Surface Modification and Superhydrophobicity ; Adhesion, Friction, and Surface Interactions ; Advanced Sensor and Energy Harvesting Materials
Authors: Soshi Nishino | Koji Hirano | Masahiro Miura
Source: Chemistry - A European Journal (article, 2020-04-21)
Field: Chemistry — Organic Chemistry

Cu‐Catalyzed Reductive <i>gem</i>‐Difunctionalization of Terminal Alkynes via Hydrosilylation/Hydroamination Cascade: Concise Synthesis of α‐Aminosilanes A copper-catalyzed reductive gem-difunctionalization of terminal alkynes with hydrosilanes and hydroxylamines has been developed. The reaction proceeds via hydrosilylation/hydroamination cascade, and the readily available and simple terminal alkynes can be transformed into the corresponding α-aminosilanes of medicinal interest in a single operation. Additionally, the use of chiral bisphosphine ligand successfully makes the reaction enantioselective to deliver the optically active α-aminosilanes with good enantiomeric ratios. Hydroamination ; Hydrosilylation ; Chemistry ; Catalysis ; Combinatorial chemistry ; Enantioselective synthesis ; Enantiomer ; Ligand (biochemistry) ; Enantiomeric excess ; Optically active ; Cascade reaction ; Organic chemistry ; Receptor Catalytic C–H Functionalization Methods ; Organoboron and organosilicon chemistry ; Catalytic Cross-Coupling Reactions
Authors: Mohamed S. A. Darwish | Hohyeon Kim | Hwangjae Lee | Chiseon Ryu | Jae Young Lee | Jungwon Yoon
Source: Nanomaterials (article, 2020-05-21)
Field: Materials Science — Materials Chemistry

Engineering Core-Shell Structures of Magnetic Ferrite Nanoparticles for High Hyperthermia Performance Magnetic ferrite nanoparticles (MFNs) with high heating efficiency are highly desirable for hyperthermia applications. As conventional MFNs usually show low heating efficiency with a lower specific loss power (<i>SLP</i>), extensive efforts to enhance the <i>SLP</i> of MFNs have been made by varying the particle compositions, sizes, and structures. In this study, we attempted to increase the <i>SLP</i> values by creating core-shell structures of MFNs. Accordingly, first we synthesized three different types of core ferrite nanoparticle of magnetite (mag), cobalt ferrite (cf) and zinc cobalt ferrite (zcf). Secondly, we synthesized eight bi-magnetic core-shell structured MFNs; Fe<sub>3</sub>O<sub>4</sub>@CoFe<sub>2</sub>O<sub>4</sub> (mag@cf<sub>1</sub>, mag@cf<sub>2</sub>), CoFe<sub>2</sub>O<sub>4</sub>@Fe<sub>3</sub>O<sub>4</sub> (cf@mag<sub>1</sub>, cf@mag<sub>2</sub>), Fe<sub>3</sub>O<sub>4</sub>@ZnCoFe<sub>2</sub>O<sub>4</sub> (mag@zcf<sub>1</sub>, mag@zcf<sub>2</sub>), and ZnCoFe<sub>2</sub>O<sub>4</sub>@Fe<sub>3</sub>O<sub>4</sub> (zcf@mag<sub>1</sub>, zcf@mag<sub>2</sub>), using a modified controlled co-precipitation process. <i>SLP</i> values of the prepared core-shell MFNs were investigated with respect to their compositions and core/shell dimensions while varying the applied magnetic field strength. Hyperthermia properties of the prepared core-shell MFNs were further compared to commercial magnetic nanoparticles under the safe limits of magnetic field parameters (<5 × 10<sup>9</sup> A/(m·s)). As a result, the highest <i>SLP</i> value (379.2 W/g<sub>metal</sub>) was obtained for mag@zcf<sub>1</sub>, with a magnetic field strength of 50 kA/m and frequency of 97 kHz. On the other hand, the lowest <i>SLP</i> value (1.7 W/g<sub>metal</sub>) was obtained for cf@mag<sub>1</sub>, with a magnetic field strength of 40 kA/m and frequency of 97 kHz. We also found that magnetic properties and thickness of the shell play critical roles in heating efficiency and hyperthermia performance. In conclusion, we successfully enhanced the <i>SLP</i> of MFNs by engineering their compositions and dimensions. Ferrite core ; Materials science ; Ferrite (magnet) ; Nanoparticle ; Magnetite ; Magnetic nanoparticles ; Magnetic core ; Nuclear magnetic resonance ; Magnetic field ; Magnetic hyperthermia ; Analytical Chemistry (journal) ; Composite material ; Nanotechnology ; Chemistry ; Metallurgy ; Physics ; Chromatography ; Electromagnetic coil Magnetic Properties and Synthesis of Ferrites ; Nanoparticle-Based Drug Delivery ; Characterization and Applications of Magnetic Nanoparticles
Authors: William W. Cobern | Betty Adams
Source: International Journal of Assessment Tools in Education (article, 2020-08-21)
Field: Chemistry — Physical and Theoretical Chemistry

Establishing survey validity: A practical guide What follows is a practical guide for establishing the validity of a survey for research purposes. The motivation for providing this guide is our observation that researchers, not necessarily being survey researchers per se, but wanting to use a survey method, lack a concise resource on validity. There is far more to know about surveys and survey construction than what this guide provides; and this guide should only be used as a starting point. However, for the needs of many researchers, this guide provides sufficient, basic information on survey validity. The guide, furthermore, includes references to important handbooks for researchers needing further information. Survey research ; Resource (disambiguation) ; Survey instrument ; Survey methodology ; Point (geometry) ; Computer science ; Psychology ; Applied psychology ; Mathematics ; Statistics Various Chemistry Research Topics ; Science Education and Pedagogy
Authors: M. Gastegger | A. McSloy | M. Luya | K. T. Schütt | R. J. Maurer
Source: The Journal of Chemical Physics (article, 2020-07-28)
Field: Materials Science — Materials Chemistry

A deep neural network for molecular wave functions in quasi-atomic minimal basis representation The emergence of machine learning methods in quantum chemistry provides new methods to revisit an old problem: Can the predictive accuracy of electronic structure calculations be decoupled from their numerical bottlenecks? Previous attempts to answer this question have, among other methods, given rise to semi-empirical quantum chemistry in minimal basis representation. We present an adaptation of the recently proposed SchNet for Orbitals (SchNOrb) deep convolutional neural network model [K. T. Schütt et al., Nat. Commun. 10, 5024 (2019)] for electronic wave functions in an optimized quasi-atomic minimal basis representation. For five organic molecules ranging from 5 to 13 heavy atoms, the model accurately predicts molecular orbital energies and wave functions and provides access to derived properties for chemical bonding analysis. Particularly for larger molecules, the model outperforms the original atomic-orbital-based SchNOrb method in terms of accuracy and scaling. We conclude by discussing the future potential of this approach in quantum chemical workflows. Wave function ; Basis (linear algebra) ; Representation (politics) ; Atomic orbital ; Convolutional neural network ; Deep learning ; Quantum ; Artificial neural network Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Advanced Physical and Chemical Molecular Interactions
Authors: Brian Gallagher | Matthew Rever | Donald Loveland | T. Nathan Mundhenk | Brock Beauchamp | Emily Robertson | Golam Gause Jaman | Anna M. Hiszpanski | T. Yong-Jin Han
Source: Materials & Design (article, 2020-02-05)
Field: Materials Science — Materials Chemistry

Predicting compressive strength of consolidated molecular solids using computer vision and deep learning We explore the application of computer vision and machine learning (ML) techniques to predict material properties (e.g., compressive strength) based on SEM images. We show that it's possible to train ML models to predict materials performance based on SEM images alone, demonstrating this capability on the real-world problem of predicting uniaxially compressed peak stress of consolidated molecular solids samples. Our image-based ML approach reduces mean absolute percentage error (MAPE) by an average of 24% over baselines representative of the current state-of-the-practice (i.e., domain-expert's analysis and correlation). We compared two complementary approaches to this problem: (1) a traditional ML approach, random forest (RF), using state-of-the-art computer vision features and (2) an end-to-end deep learning (DL) approach, where features are learned automatically from raw images. We demonstrate the complementarity of these approaches, showing that RF performs best in the “small data” regime in which many real-world scientific applications reside (up to 24% lower RMSE than DL), whereas DL outpaces RF in the “big data” regime, where abundant training samples are available (up to 24% lower RMSE than RF). Finally, we demonstrate that models trained using machine learning techniques are capable of discovering and utilizing informative crystal attributes previously underutilized by domain experts. Random forest ; Artificial intelligence ; Mean squared error ; Machine learning ; Complementarity (molecular biology) ; Mean absolute error ; Pattern recognition (psychology) ; Computer science ; Deep learning ; Compressive strength ; Mean absolute percentage error ; Domain knowledge ; Materials science ; Artificial neural network ; Statistics ; Mathematics ; Composite material Machine Learning in Materials Science ; Mineral Processing and Grinding ; X-ray Diffraction in Crystallography